- Lisa_teatalk - mailman.iro.umontreal.ca

Schedule of Talks before and after NIPS 2014
by Kyung Hyun Cho 14 Déc '14

14 Déc '14

Dear all, We will have a number of visitors at the lab before and after NIPS 2014. Many of the talks will be interesting to many of the lab members, and I would like to recommend all to be at all of the talks. Also, I'd like to warmly welcome anyone on this mailing list who's not at the LISA lab to attend the talks. Most of the talks will be held at AA3195 (Pavillon André-Aisenstadt, 2920 Chemin de la tour, Montréal). Please, check back frequently for the locations of the talks on http://lisa.iro.umontreal.ca/seminars_en.html. There may be a few more talks added in a next few days, so again, please check the schedule online frequently. Best, - Cho *= Schedule = * + *3 Dec 2014* (Wed) - 13.30 - 14.30 <A Multiplicative Model for Learning Distributed Text-Based Attribute Representations> by Ryan Kiros (University of Toronto) + *4 Dec 2014* (Thu) - 10.30 - 11.30 <What if computer can perceive the world like we do?> by Xinyi Chen, Peng (Eric) Ding (DeepGlint) - 13.30 - 14.30 <Learning Compact Yet Rich Models for Text> by Sarath Chandar (IBM India) + *5 Dec 2014* (Fri) - 10.30 - 11.30 <Joint Training of Deep Autoencoders> by Dr. Yingbo Zhou (University at Buffalo, The State University of New York) - 13.30 - 14.30 <How Watson Learns Superhuman Jeopardy! Strategies> by Dr. Gerald Tesauro (IBM T. J. Watson Research Center) + *15 Dec 2014* (Mon) - 13.30 - 14.30 <TBD> by Prof. Yung-Kyun Noh (KAIST) + *16 Dec 2014* (Tue) - 13.30 - 14.30 <General Stochastic Networks for Classification> by Matthias Zohrer (TU Graz)

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[URGEN] Re: Schedule of Talks before and after NIPS 2014
by Kyung Hyun Cho 04 Déc '14

04 Déc '14

Dear all, I made a huge mistake in the last email announcing that the talk this afternoon will be at AA3195. That is wrong! The talk will start in *20 min* at *Z-209* in the main building (Roger Gaudry). Sorry about the confusion! - Cho On Wed, Dec 3, 2014 at 7:46 PM, Kyung Hyun Cho <cho.k.hyun(a)gmail.com> wrote: > Dear all, > > This is a reminder of *two* talks scheduled tomorrow. The first talk will > be given by Xinyi Chen and Peng (Eric) Ding from DeepGlint. The second talk > will be given by Sarath Chandar from IBM India. > > Both of these talks will be at AA3195. The first one starts at 10.30, and > the second one at 13.30. > > Hope to see many of you there! > - Cho > > P.S. I will probably prepare snacks only for the afternoon's talk, unless > anyone objects. Anyone who objects to this is kindly asked to bring snacks > for everyone to the morning's talk :) > > *= Schedule =* > > Available also at: http://lisa.iro.umontreal.ca/seminars_en.html > > *+ 3 Dec 2014 (Wed)* > - 13.30 - 14.30 <A Multiplicative Model for Learning Distributed > Text-Based Attribute Representations> by Ryan Kiros (University of Toronto) > > *+ 4 Dec 2014 (Thu)* > - 10.30 - 11.30 <What if computer can perceive the world like we do?> by > Xinyi Chen, Peng (Eric) Ding (DeepGlint) > - 13.30 - 14.30 <Learning Compact Yet Rich Models for Text> by Sarath > Chandar (IBM India) > > *+ 5 Dec 2014 (Fri)* > - 10.30 - 11.30 <Joint Training of Deep Autoencoders> by Dr. Yingbo Zhou > (University at Buffalo, The State University of New York) > - 13.30 - 14.30 <How Watson Learns Superhuman Jeopardy! Strategies> by > Dr. Gerald Tesauro (IBM T. J. Watson Research Center) > > *+ 15 Dec 2014 (Mon)* > - 10.30 - 11.30 <On the Number of Linear Regions of Deep Neural > Networks> by Dr. Guido Montufar <MPI MIS> > - 13.30 - 14.30 <Machine Learning with Nearest Neighbors> by Prof. > Yung-Kyun Noh (KAIST) > > *+ 16 Dec 2014 (Tue)* > - 13.30 - 14.30 <General Stochastic Networks for Classification> by > Matthias Zohrer (TU Graz) > > >

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Tea Talk 26 Nov Wed @13.30 AA3195 by Antoine Chassang
by Kyung Hyun Cho 25 Nov '14

25 Nov '14

Dear all, Antoine Chassang will tell us about his work on face detection during his internship at the LISA lab. The talk will be held at the usual place AA3195 starting from 13.30 next Wednesday (26 Nov). Hope to see many of you at the talk! - Cho === - Speaker: Antoine Chassang - Date/Time: 26 Nov (Wed) 13.30 - 14.30 - Place: AA3195 - Title: Face Detection - Abstract: Whereas the state of the art is relying on viewpoint-specialized models which need additional pose-related annotations, we trained convolutional networks on a large dataset (700k faces extracted from Google Images) to learn invariance to pose. We evaluated our method on FDDB, a standard benchmark for face detection, and we show that we can achieve state of the art performance. To speed up the inference, we investigated model compression using a teacher-student formulation where the student network learns to reproduce the teacher output. The compressed model is deeper and thinner, with less parameters than the teacher.

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Talk 5 Dec Fri @13.30 AA3195 by Dr. Gerald Tesauro
by Kyung Hyun Cho 21 Nov '14

21 Nov '14

Dear all, This is an early reminder of the talk by Dr. Gerald Tesauro from IBM Research Center on *5 Dec *(Friday) starting from 13.30 at AA3195. He will tell us about the exciting story behind how Watson beat human competitors on Jeopardy!. Best, - Cho P.S. From now on, you can check the schedules of the future (and past) seminars at http://lisa.iro.umontreal.ca/seminars_en.html. The same page in French will appear soon. === - Speaker: Dr. Gerald Tesauro (IBM TJ Watson Research Center) - Date/Time: 13.30 - 14.30, 5 Dec - Place: AA3195 - Title: How Watson Learns Superhuman Jeopardy! Strategies - Abstract: Major advances in Question Answering technology were needed for Watson to play "Jeopardy!" at championship level -- the show requires rapid-fire answers to challenging natural language questions, broad general knowledge, high precision, and accurate confidence estimates. In addition, Jeopardy! features four types of decision making carrying great strategic importance: (1) selecting the next clue when in control of the board; (2) deciding whether to attempt to buzz in; (3) wagering on Daily Doubles; (4) wagering in Final Jeopardy. This talk describes how Watson makes the above decisions using innovative quantitative methods that, in principle, maximize Watson's overall winning chances. We first describe our development of faithful simulation models of human contestants and the Jeopardy! game environment. We then present specific learning/optimization methods used in each strategy algorithm: these methods span a range of popular AI research topics, including Bayesian inference, game theory, Dynamic Programming, Reinforcement Learning, and real-time "rollouts." Application of these methods yielded superhuman game strategies for Watson that significantly enhanced its overall competitive record. Joint work with David Gondek, Jon Lenchner, James Fan and John Prager. - Speaker Bio: Gerald Tesauro is a Research Staff Member at IBM's TJ Watson Research Center. He is best known for creating TD-Gammon, a self-teaching neural network that learned to play backgammon at human world championship level. He has also worked on theoretical and applied machine learning in a wide variety of other settings, including multi-agent learning, dimensionality reduction, computer virus recognition, computer chess (Deep Blue), intelligent e-commerce agents and autonomic computing. Dr. Tesauro serves on the NIPS Foundation Board of Directors, and was recently elected AAAI Fellow.

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Talk 21 Nov Fri @15.00 AA3195 by Dr. John Hershey
by Kyung Hyun Cho 21 Nov '14

21 Nov '14

Dear all, Dr. John Hershey (Mistubishi Electric Research Labs, US) will tell us about the connection between model-free approaches (e.g. deep neural networks) and model-based approaches (e.g. probabilistic graphical models) and how we can utilize this connection. His talk will start from 15.00 next Friday (21 Nov) at the usual place AA3195. Hope to see many of you there! - Cho === - Speaker: Dr. John Hershey (Mistubishi Electric Research Labs) - Date/Time: 15.00 - 16.00, 21 Nov - Place: AA3195 - Title: Deep Unfolding: Infusing Deep Architectures with Generative Model Inference - Abstract: Model-based methods and deep neural networks have both been tremendously successful paradigms in machine learning. In model-based methods, problem domain knowledge can be built into the constraints of the model, typically at the expense of difficulties during inference. In contrast, deterministic deep neural networks are constructed in such a way that inference is straightforward, but their architectures are rather generic and it can be unclear how to incorporate problem domain knowledge. This work aims to obtain the advantages of both approaches. To do so, we start with a model-based approach and unfold the iterations of its inference method to form a layer-wise structure. We then decouple the model parameters across layers to increase the network's learning capacity. This results in novel neural-network-like architectures that incorporate our model-based constraints, but can be trained discriminatively to perform fast and accurate inference. We show how this framework can be applied to a non-negative matrix factorization model to obtain a new kind of non-negative deep neural network, that can be trained using a multiplicative backpropagation-style update algorithm. We present speech enhancement experiments showing that our approach is competitive with conventional neural networks despite using far fewer parameters. - Bio: John Hershey is a researcher at Mistubishi Electric Research Labs (MERL), in Cambridge, MA since 2010. Prior to that, John spent 5 years as a researcher at IBM's Watson Research Center in New York, in the Speech Algorithms and Engines group, and one year as visiting researcher in the speech group at Microsoft Research, in Redmond, WA. His obtained his Ph.D. at the University of California, San Diego. He is currently working on machine learning for signal enhancement and separation, speech recognition, language processing, and adaptive user interfaces.

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Fwd: ***AUJOURD'HUI*** : COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC / Martin Wainwright
by Yoshua Bengio 20 Nov '14

20 Nov '14

Reminder: one of the highest-profile machine learning researchers is speaking at 4pm in PAA 1360. ---------- Forwarded message ---------- From: <crm(a)crm.umontreal.ca> Date: Thu, Nov 20, 2014 at 9:46 AM Subject: ***AUJOURD'HUI*** : COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC / Martin Wainwright To: activites(a)crm.umontreal.ca ****************************************************************** COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC Montréal ****************************************************************** DATE : Le jeudi 20 novembre 2014 / Thursday, November 20, 2014 HEURE / TIME : 16 h / 4:00 p.m. CONFERENCIER(S) / SPEAKER(S) : Martin Wainwright (University of California, Berkeley) TITRE / TITLE : High-dimensional phenomena in mathematical statistics and convex analysis LIEU / PLACE : CRM, UdeM, Pav. André-Aisenstadt, 2920, ch. de la Tour, salle 1360 RESUME / ABSTRACT : Statistical models in which the ambient dimension is of the same order or larger than the sample size arise frequently in different areas of science and engineering. Although high-dimensional models of this type date back to the work of Kolmogorov, they have been the subject of intensive study over the past decade, and have interesting connections to many branches of mathematics (including concentration of measure, random matrix theory, convex geometry, and information theory). In this talk, we provide a broad overview of the general area, including vignettes on phase transitions in high-dimensional graph recovery, and randomized approximations of convex programs. ****************************************************************** Un café sera servi à 15h30 / Coffee will be served at 3:30 pm ****************************************************************** http://www.crm.umontreal.ca/Colloques/colloqueSMQ-Montreal.html

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Fwd: COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC (20/11/2014, Martin Wainwright)
by Yoshua Bengio 17 Nov '14

17 Nov '14

Martin Wainwright is an outstanding machine learning researcher and he gives a talk Thursday at 4pm room 1360. Don't miss it! ---------- Forwarded message ---------- From: <crm(a)crm.umontreal.ca> Date: Mon, Nov 17, 2014 at 10:32 AM Subject: COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC (20/11/2014, Martin Wainwright) To: activites(a)crm.umontreal.ca ****************************************************************** COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC Montréal ****************************************************************** DATE : Le jeudi 20 novembre 2014 / Thursday, November 20, 2014 HEURE / TIME : 16 h / 4:00 p.m. CONFERENCIER(S) / SPEAKER(S) : Martin Wainwright (University of California, Berkeley) TITRE / TITLE : High-dimensional phenomena in mathematical statistics and convex analysis LIEU / PLACE : CRM, UdeM, Pav. André-Aisenstadt, 2920, ch. de la Tour, salle 1360 RESUME / ABSTRACT : Statistical models in which the ambient dimension is of the same order or larger than the sample size arise frequently in different areas of science and engineering. Although high-dimensional models of this type date back to the work of Kolmogorov, they have been the subject of intensive study over the past decade, and have interesting connections to many branches of mathematics (including concentration of measure, random matrix theory, convex geometry, and information theory). In this talk, we provide a broad overview of the general area, including vignettes on phase transitions in high-dimensional graph recovery, and randomized approximations of convex programs. ****************************************************************** Un café sera servi à 15h30 / Coffee will be served at 3:30 pm ****************************************************************** http://www.crm.umontreal.ca/Colloques/colloqueSMQ-Montreal.html

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Tea Talk 12 Nov Wed @15.00 AA3195 by Nicolas Chapados
by Kyung Hyun Cho 12 Nov '14

12 Nov '14

Dear all, Nicolas Chapados (ApSTAT Technology, Ph.D. from LISA Lab) will tell us about his latest work on modelling the time series of integer counts, which was presented at ICML 2014 this year. The talk will be held at the usual place AA3195, but will *start at 15.00*. Hope to see many of you at the talk! - Cho === - Speaker: Dr. Nicolas Chapados, ApSTAT Technology - Date/Time: 12 Nov (Wed) 15.00 - 16.00 - Place: AA3195 - Title: Effective Bayesian Modeling of Groups of Related Count Time Series - Abstract: Time series of integer count data arise in a wide variety of practical situations: the number of clicks on an URL in a given time span, the time-dependent consumer demand for pink T-shirts at a fashion store, or the number of spare parts needed to keep a fleet of fighter jets in working order on an aircraft carrier. When these counts are either small, highly variable or contain a large number of zero values — the signature of rare events — classical time series models are grossly misspecified and often yield unreasonable forecast distributions. In this talk, I describe a hierarchical probabilistic state-space model for count data, for which approximate Bayesian inference is simple and fast. The model can handle arbitrary explanatory variables and recognizes the common scenario of “weak coupling” between a group of related time series (e.g. the demand for a seasonal product at several stores of the same chain should share similar seasonal patterns without necessarily exhibiting strong cross-correlations). I illustrate the forecasting performance on a number of benchmarks from supply chain planning, although the range of applicability of the approach is much wider. I also show that the model can extrapolate useful seasonalities from extremely short time series (only 4 observations!) by automatically borrowing statistical strength from related longer series. This work was presented at the ICML’14 conference in Beijing, last June.

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Tea Talk 5 Nov Wed @13.30 AA3195 by Li Yao
by Kyung Hyun Cho 03 Nov '14

03 Nov '14

Dear all, Li will tell us about exciting recent developments on integrating attention mechanisms to neural networks on Wednesday. The talk will be held at the usual place AA3195 and usual time of 13.30. Hope to see many of you there! === - Speaker: Li Yao - Title: Learning where to look - Abstract: This talk focuses on computational models of "learning where to look". There has been some recent work in this direction using feedforward/recurrent neural networks, Boltzmann machines, neural autoregressive density estimators, and inevitably some reinforcement learning techniques. This talk will start with this paper "Recurrent models of visual attention" (NIPS14). The ideas from other related papers will also be briefly discussed.

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Tea Talk 29 Oct Wed @13.30 AA3195 by Dong-Hyun Lee
by Kyung Hyun Cho 29 Oct '14

29 Oct '14

Dear all, Dong-Hyun will update us on the progress in using target-prop this week at the tea talk. The talk will be held at the usual place AA3195 and usual time of 13.30. Hope many will attend the talk! - Cho === - Speaker: Dong-Hyun Lee - Title: Training supervised deep network and an auto-encoder through target propagation without back-prop - Abstract: I'll present how to train supervised network through target propagation. This new technique suggested by Yoshua can make it possible to train deep network without back propagation thanks to layer-wise target matching losses and target propagation through layers. Our results are comparable to back-propagation on MNIST. And we can train discrete networks directly which is impossible to train using ordinary back-propagation because this technique doesn't use any derivatives for propagating training signals. Using this, we can also train an auto-encoder without back-prop.

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Slides and code
by David Krueger 22 Oct '14

22 Oct '14

Hey everyone, Here are the slides: https://docs.google.com/presentation/d/1Pp_Rga2qYUnDtkxYwHtda9aTIvEwIvgClkY… and code is attached. It basically just lets you make plots of kernel functions, sample from a Gaussian Process (conditional or not), and evaluate the conditional distribution of Gaussian Process. Let me know if you have *any* questions about the code or the talk. I'm more than happy to discuss it.

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Tea Talk 22 Oct Wed TOMORROW @13.30 AA3195 by David Krueger
by Kyung Hyun Cho 21 Oct '14

21 Oct '14

Dear all, Tomorrow David Krueger will tell us about Bayesian optimization method based on a recent paper <Freeze-Thaw Bayesian Optimization> (Swesky, Snoek and Adams, 2014) at the usual place AA3195. Sorry about a late announcement due to my travel! - Cho === - Speaker: David Krueger - Date and Place: 13.30 - 14.30, 22 Oct (Wed) at AA3195 - Title: Freeze-Thaw Bayesian Optimization (Swesky, Snoek and Adams, 2014)

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Tea Talk 16 Oct Thu @16.30 P-312 by Mehdi Molkaraie
by Kyung Hyun Cho 13 Oct '14

13 Oct '14

Dear all, This week on Thursday, Dr. Mehdi Molkaraie (UPF Barcelona, Spain) will visit our lab and tell us about his work done at ETH Zurich, Switzerland together with Prof. Andi Loeliger. Note that the talk will start at *16.30* on *Thursday* in *P-312* (Pavillon Roger-Gaudry). Hope to see many of you there! - Cho === - Speaker: Dr. Mehdi Molkaraie, UPF Barcelona, Spain - Date and Place: 16.30 - 17.30, 16 Oct (Thu) at P-312 (Pavillon Roger-Gaudry) - Title: Partition Function of the Ising Model via Factor Graph Duality - Abstract: The partition function of a factor graph and the partition function of the dual factor graph are related to each other by the normal factor graph duality theorem. We apply this result to the classical problem of computing the partition function of the Ising model to show that, at low temperature, Monte Carlo methods are more efficient in the dual graphical model than the original graphical model. The viability of the methods is demonstrated by numerical experiments. Based on a joint work with Prof H.-A. Loeliger (ETH-Zurich, Switzerland) Two related articles are available on arXiv at: http://arxiv.org/abs/1307.3645 http://arxiv.org/abs/1401.4912 Slides are available at: https://drive.google.com/file/d/0B16RwCMQqrtdc1lybnBfSC1tQUw4M2xMRHkyZUttbD…

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Tea Talk 8 Oct Wed @13.30 AA3195 by Jan Chorowski
by Kyung Hyun Cho 08 Oct '14

08 Oct '14

Dear all, On Wednesday (8 Oct), Jan Chorowski will tell us about his latest work on building an end-to-end speech recognition system using attention mechanism. This work has been submitted to NIPS Deep Learning Workshop 2014, and the submitted manuscript is attached. Hope to see many of you there! - K === - Title: End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results - Spaker: Prof. Jan Chorowski, University of Wrocław, Poland - Date and Place: 13.30-14.30, 8 Oct (Wednesday) @AA3195 - Abstract: We replace the Hidden Markov Model (HMM) which is traditionally used in in continuous speech recognition with a bi-directional recurrent neural network en- coder coupled to a recurrent neural network decoder that directly emits a stream of phonemes. The alignment between the input and output sequences is established using an attention mechanism: the decoder emits each symbol based on a context created with a subset of input symbols selected by the attention mechanism. We report initial results demonstrating that this new approach achieves phoneme error rates that are comparable to the state-of-the-art HMM-based decoders, on the TIMIT dataset.

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Fwd: Damien Ernst talk, ***Wed October 8***, 2pm, MC 437
by Yoshua Bengio 03 Oct '14

03 Oct '14

---------- Forwarded message ---------- From: Doina Precup <dprecup(a)cs.mcgill.ca> Date: Fri, Oct 3, 2014 at 2:14 PM Subject: Damien Ernst talk, ***Wed October 8***, 2pm, MC 437 To: "labrl(a)cs.mcgill.ca" <labrl(a)cs.mcgill.ca>, Bengio Yoshua < bengioy(a)iro.umontreal.ca> Cc: "dernst(a)ulg.ac.be" <dernst(a)ulg.ac.be> Hi everyone, Damien Ernst (http://www.montefiore.ulg.ac.be/~ernst/) will be visiting us the coming Wed. He will give a talk at 2pm in MC 437, titled: Batch Mode Reinforcement Learning based on the Synthesis of Artificial Trajectories Abstract: We consider the batch mode reinforcement learning setting, where the central problem is to learn from a sample of trajectories a policy that satisfies or optimizes a performance criterion. We focus on the continuous state space case for which usual resolution schemes rely on function approximators either to represent the underlying control problem or to represent its value function. As an alternative to the use of function approximators, we rely on the synthesis of “artificial trajectories” from the given sample of trajectories, and show that this idea opens new avenues for designing and analyzing algorithms for batch mode reinforcement learning. Best, Doina

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Fwd: **AUJOURD'HUI** : COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC / Paul Bourgade
by Yoshua Bengio 02 Oct '14

02 Oct '14

Potentially interesting math talk today about the eigenspectrum of random matrices: ---------- Forwarded message ---------- From: <CRM(a)crm.umontreal.ca> Date: Thu, Oct 2, 2014 at 9:15 AM Subject: **AUJOURD'HUI** : COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC / Paul Bourgade To: activites(a)crm.umontreal.ca ****************************************************************** COLLOQUE DES SCIENCES MATHÉMATIQUES DU QUÉBEC ****************************************************************** DATE : Le jeudi 2 octobre 2014 / Thursday, October 2, 2014 HEURE / TIME : 16 h / 4:00 p.m. CONFERENCIER(S) / SPEAKER(S) : Paul Bourgade (New York University) TITRE / TITLE : Universality in random matrix theory LIEU / PLACE : CRM, UdeM, Pav. André-Aisenstadt, 2920, ch. de la Tour, salle 6214 RESUME / ABSTRACT : Wigner stated the general hypothesis that the distribution of eigenvalue spacings of large complicated quantum systems is universal, in the sense that it depends only on the symmetry class of the physical system but not on other detailed structures. The simplest case for this hypothesis concerns large but finite dimensional matrices. I will explain some historical aspects random matrix theory, as well as recent techniques developed to prove eigenvalues and eigenvectors universality, for matrices with independent entries from all symmetry classes. The methods are both probabilist (random walks and coupling) and analytic (homogenization for parabolic PDEs). ****************************************************************** Un café sera servi à 15h30 / Coffee will be served at 3:30 pm ****************************************************************** http://www.crm.umontreal.ca/Colloques/index.html

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[UPDATE] Tea Talk 1 Oct Wed @13.30 AA3195 by Felix Hill
by Kyung Hyun Cho 29 Sep '14

29 Sep '14

Dear all, The date of the upcoming teatalk has changed from Thursday to Wednesday. Best, - Cho === - Title: Syntax isn't a thing, and other shocking insights: what deep learning tells us about language - Speaker: Felix Hill, University of Cambridge - Date and Place: 13.30 - 14.30, 1 Oct (Wednesday) @AA3195 - Abstract: [redacted by the organizer due to its shocking nature] On Fri, Sep 26, 2014 at 8:04 PM, Kyung Hyun Cho <cho.k.hyun(a)gmail.com> wrote: > Dear all, > > On Thursday (2 Oct), Felix Hill will tell us some shocking secrets about > natural languages, possibly related to why foreign language education in > Korea which puts huge focus on learning/memorizing grammar rules has > horribly failed. The talk will be at the usual place AA3195. > > Hope to see many of you there! > - Cho > > === > - Title: Syntax isn't a thing, and other shocking insights: what deep > learning tells us about language > - Speaker: Felix Hill, University of Cambridge > - Date and Place: 2 Oct (Thursday) at AA3195 > - Abstract: > [redacted by the organizer due to its shocking nature] > >

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Tea Talk 2 Oct Thu @13.30 AA3195 by Felix Hill
by Kyung Hyun Cho 27 Sep '14

27 Sep '14

Dear all, On Thursday (2 Oct), Felix Hill will tell us some shocking secrets about natural languages, possibly related to why foreign language education in Korea which puts huge focus on learning/memorizing grammar rules has horribly failed. The talk will be at the usual place AA3195. Hope to see many of you there! - Cho === - Title: Syntax isn't a thing, and other shocking insights: what deep learning tells us about language - Speaker: Felix Hill, University of Cambridge - Date and Place: 2 Oct (Thursday) at AA3195 - Abstract: [redacted by the organizer due to its shocking nature]

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Tea Talk 24 Sep Wednesday @13.30 AA3195 by Jyri Kivinen
by Kyung Hyun Cho 22 Sep '14

22 Sep '14

Dear all, On Wednesday (24 Sep), Jyri Kivinen will tell us about variational autoencoders at the usual place AA3195. Hope to see many of you there! - Cho ===== - Title: Autoencoding Variational Bayes - Speaker: Jyri Kivinen - Date and Place: 24 Sep (Wednesday) at AA3195 - Abstract: I will present and discuss the auto-encoding variational Bayes approach proposed in Kingma and Welling [2014]. http://arxiv.org/abs/1312.6114

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Tea Talk 17 Sep Wednesday @13.30 AA3195 by Kyle Kastner
by Kyung Hyun Cho 12 Sep '14

12 Sep '14

Dear all, We will have a tea talk next Wednesday from 13.30 at AA3195 by Kyle Kastner. He will tell us about his recent project, sklearn-theano <http://sklearn-theano.github.io/> which implements a nice interface in scikit-learn to load and use neural network models that were trained using various other software packages including Theano. Also, he will share his experience of using Theano and pylearn2 before joining LISA. Hope to see many of you there! - Cho

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Tea Talk 10 Sep Wednesday (TODAY!) @13.30 AA3195 by Matthieu Courbariaux
by Kyung Hyun Cho 10 Sep '14

10 Sep '14

Dear all, This is a reminder of the tea talk we have today at 13.30. I hope to see many of you there! - K On Mon, Sep 8, 2014 at 6:52 PM, Kyung Hyun Cho <cho.k.hyun(a)gmail.com> wrote: > Dear all, > > Matthieu Courbariaux will tell us about how to program fPGA with OpenCL > this Wednesday at 13.30 in a usual tea talk place (AA3195). > > Best, > - Cho > >

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Re: [Lisa_teatalk] [Lisa_labo] Call for teatalk speakers
by Kyung Hyun Cho 09 Sep '14

09 Sep '14

Nicolas, I've scheduled you on the second week of November. Thanks for volunteering! Please, send me the title and abstract of the talk, say, at least two weeks in advance. Best, - Cho On Mon, Sep 8, 2014 at 11:27 PM, Nicolas Chapados <chapados(a)iro.umontreal.ca > wrote: > Kyung Hyun, can you schedule me for the second week of November? I’m away > in Mexico the week after, and in China before… :-) > > Thanks! > + Nicolas > > --- > Nicolas Chapados, Ph.D., CFA > www.chapados.ca > > Le 2014-09-08 à 18:57, Kyung Hyun Cho <cho.k.hyun(a)gmail.com> a écrit : > > Dear all, > > We have about 7 tea talk slots available before NIPS (until the end of > November). If anyone's willing to present at the teatalk, don't hesitate to > contact me! > > You can either (1) tell the lab about your research, (2) present some > others' work or (3) share interesting research/development ideas. If you > want to give a tea talk but are not sure which topic or existing paper to > present, come talk to me and we'll figure something out. > > Best, > - Cho > _______________________________________________ > Lisa_labo mailing list > Lisa_labo(a)iro.umontreal.ca > https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo > > >

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Re: [Lisa_teatalk] [Lisa_labo] Tea Talk 10 Sep Wednesday @13.30 AA3195 by Matthieu Courbariaux
by Kyung Hyun Cho 09 Sep '14

09 Sep '14

I will ask the speaker about the slides. If he's okay with it, I will share it on this mailing list after the talk. On Tue, Sep 9, 2014 at 10:58 AM, Vincent Dumoulin <dumouliv(a)iro.umontreal.ca > wrote: > Same thing for me, I'm very interested in hearing about it but won't be > able to be there. > > -- > Vincent Dumoulin, B.Sc. Physique et Informatique > Étudiant au Ph.D. > LISA, Université de Montréal > Bureau: 3336, pavillon André-Aisenstadt > vincent.dumoulin(a)umontreal.ca > > On Mon, Sep 8, 2014 at 10:46 PM, Eric Martin <emartin(a)caltech.edu> wrote: > >> If there are slides, could they be sent out after the talk? I won't be >> able to attend the talk, but I'm interested in the topic. >> >> -Eric >> On Sep 8, 2014 3:54 PM, "Kyung Hyun Cho" <cho.k.hyun(a)gmail.com> wrote: >> >>> Dear all, >>> >>> Matthieu Courbariaux will tell us about how to program fPGA with OpenCL >>> this Wednesday at 13.30 in a usual tea talk place (AA3195). >>> >>> Best, >>> - Cho >>> >>> >>> _______________________________________________ >>> Lisa_labo mailing list >>> Lisa_labo(a)iro.umontreal.ca >>> https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo >>> >>> >> _______________________________________________ >> Lisa_labo mailing list >> Lisa_labo(a)iro.umontreal.ca >> https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo >> >> >

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Re: [Lisa_teatalk] [Lisa_labo] Call for teatalk speakers
by Kyung Hyun Cho 09 Sep '14

09 Sep '14

Sounds great! I've booked you on the first week of November. I'll get back to you with a fixed date later on. Don't feel pressured too much about the teatalk. Just let me know the title and abstract later. On Mon, Sep 8, 2014 at 10:42 PM, Dong-Hyun Lee <sayit78(a)gmail.com> wrote: > I can present at a teatalk in early November. I'm still not good at > speaking English now, I'll try to prepare a presentation until then. But I > haven't decided the subject yet (I have 2 ~ 3 candidates for the teatalk, > I'll pick it up later) > > Dong-Hyun. > > 2014-09-08 18:57 GMT-04:00 Kyung Hyun Cho <cho.k.hyun(a)gmail.com>: > >> Dear all, >> >> We have about 7 tea talk slots available before NIPS (until the end of >> November). If anyone's willing to present at the teatalk, don't hesitate to >> contact me! >> >> You can either (1) tell the lab about your research, (2) present some >> others' work or (3) share interesting research/development ideas. If you >> want to give a tea talk but are not sure which topic or existing paper to >> present, come talk to me and we'll figure something out. >> >> Best, >> - Cho >> >> _______________________________________________ >> Lisa_labo mailing list >> Lisa_labo(a)iro.umontreal.ca >> https://webmail.iro.umontreal.ca/mailman/listinfo/lisa_labo >> >> > > > -- > - Dong-Hyun >

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Call for teatalk speakers
by Kyung Hyun Cho 08 Sep '14

08 Sep '14

Dear all, We have about 7 tea talk slots available before NIPS (until the end of November). If anyone's willing to present at the teatalk, don't hesitate to contact me! You can either (1) tell the lab about your research, (2) present some others' work or (3) share interesting research/development ideas. If you want to give a tea talk but are not sure which topic or existing paper to present, come talk to me and we'll figure something out. Best, - Cho

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