Alex Lamb - RankMe

88 papers A* 18A 5C 1Journal 57Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Scalar Rewards to Potential Trends: Shaping Potential Landscapes for Model-Based Reinforcement Learning. CoRR Yao-Hui Li, Zeyu Wang, Xin Li, Wei Pang, Yingfang Yuan, Zhengkun Chen, Boya Zhang, Riashat Islam, Alex Lamb, Yonggang Zhang
2026	J	`jnl`	Improving Sampling for Masked Diffusion Models via Information Gain. CoRR Kaisen Yang, Jayden Teoh, Kaicheng Yang, Yitong Zhang, Alex Lamb
2026	J	`jnl`	Next Concept Prediction in Discrete Latent Space Leads to Stronger Language Models. CoRR Yuliang Liu, Yunchong Song, Yixuan Wang, Kewen Ge, Alex Lamb, Qipeng Guo, Kai Chen, Bowen Zhou, Zhouhan Lin
2026	J	`jnl`	When does predictive inverse dynamics outperform behavior cloning? CoRR Lukas Schäfer, Pallavi Choudhury, Abdelhak Lemkhenter, Chris Lovett, Somjit Nath, Luis França, Matheus Ribeiro Furtado de Mendonca, Alex Lamb, Riashat Islam, Siddhartha Sen, John Langford, Katja Hofmann, Sergio Valcarcel Macua
2025	J	`jnl`	Attention Schema-based Attention Control (ASAC): A Cognitive-Inspired Approach for Attention Management in Transformers. CoRR Krati Saxena, Federico Jurado Ruiz, Guido Manzi, Dianbo Liu, Alex Lamb
2025	J	`jnl`	Efficient Joint Prediction of Multiple Future Tokens. CoRR Kwangjun Ahn, Alex Lamb, John Langford
2025	J	`jnl`	Explore-Execute Chain: Towards an Efficient Structured Reasoning Paradigm. CoRR Kaisen Yang, Lixuan He, Rushi Shah, Kaicheng Yang, Qinwei Ma, Dianbo Liu, Alex Lamb
2025	J	`jnl`	Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance. CoRR Luozhijie Jin, Zijie Qiu, Jie Liu, Zijie Diao, Lifeng Qiao, Ning Ding, Alex Lamb, Xipeng Qiu
2025	J	`jnl`	Next-Latent Prediction Transformers Learn Compact World Models. CoRR Jayden Teoh, Manan Tomar, Kwangjun Ahn, Edward S. Hu, Pratyusha Sharma, Riashat Islam, Alex Lamb, John Langford
2025	A*	`conf`	The Belief State Transformer. ICLR Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford
2025	A*	`conf`	Towards Improving Exploration through Sibling Augmented GFlowNets. ICLR Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio
2024	J	`jnl`	Can AI Be as Creative as Humans? CoRR Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
2024	J	`jnl`	Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs. CoRR Lili Wu, Ben Evans, Riashat Islam, Raihan Seraj, Yonathan Efroni, Alex Lamb
2024	J	`jnl`	Learning to Achieve Goals with Belief State Transformers. CoRR Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford
2024	A*	`conf`	PcLast: Discovering Plannable Continuous Latent States. ICML Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miroslav Dudík, John Langford, Alex Lamb
2024	A*	`conf`	Towards Principled Representation Learning from Videos for Reinforcement Learning. ICLR Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
2024	J	`jnl`	Towards Principled Representation Learning from Videos for Reinforcement Learning. CoRR Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
2024	J	`jnl`	Video Occupancy Models. CoRR Manan Tomar, Philippe Hansen-Estruch, Philip Bachman, Alex Lamb, John Langford, Matthew E. Taylor, Sergey Levine
2023	A*	`conf`	Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
2023	J	`jnl`	Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. Trans. Mach. Learn. Res. Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
2023	J	`jnl`	Leveraging the Third Dimension in Contrastive Learning. CoRR Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer
2023	J	`jnl`	PcLast: Discovering Plannable Continuous Latent States. CoRR Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miro Dudík, John Langford, Alex Lamb
2023	A*	`conf`	Principled Offline RL in the Presence of Rich Exogenous Information. ICML Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Rajiv Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
2023	A	`conf`	Representation Learning in Deep RL via Discrete Information Bottleneck. AISTATS Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
2023	A	`conf`	Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
2022	J	`jnl`	Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
2022	J	`jnl`	Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. CoRR Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
2022	J	`jnl`	CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback. CoRR Alexia Jolicoeur-Martineau, Alex Lamb, Vikas Verma, Aniket Didolkar
2022	A*	`conf`	Coordination Among Neural Modules Through a Shared Global Workspace. ICLR Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio
2022	A*	`conf`	Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
2022	J	`jnl`	Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
2022	J	`jnl`	Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
2022	J	`jnl`	Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio
2022	J	`jnl`	Interpolation consistency training for semi-supervised learning. Neural Networks Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, Arno Solin, Yoshua Bengio, David Lopez-Paz
2022	J	`jnl`	Neural Active Learning on Heteroskedastic Distributions. CoRR Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
2022	J	`jnl`	Representation Learning in Deep RL via Discrete Information Bottleneck. CoRR Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
2022	A*	`conf`	Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. NeurIPS Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
2022	J	`jnl`	Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. CoRR Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
2022	J	`jnl`	Towards Data-Driven Offline Simulations for Online Reinforcement Learning. CoRR Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
2021	J	`jnl`	A Brief Introduction to Generative Models. CoRR Alex Lamb
2021	J	`jnl`	Coordination Among Neural Modules Through a Shared Global Workspace. CoRR Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio
2021	A*	`conf`	Discrete-Valued Neural Communication. NeurIPS Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
2021	J	`jnl`	Discrete-Valued Neural Communication. CoRR Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
2021	A*	`conf`	Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
2021	A*	`conf`	GraphMix: Improved Training of GNNs for Semi-Supervised Learning. AAAI Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
2021	A	`conf`	Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. AISTATS Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
2021	J	`jnl`	Predicting the Ordering of Characters in Japanese Historical Documents. CoRR Alex Lamb, Tarin Clanuwat, Siyu Han, Mikel Bober-Irizar, Asanobu Kitamoto
2021	A*	`conf`	Recurrent Independent Mechanisms. ICLR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2021	J	`jnl`	Transformers with Competitive Ensembles of Independent Mechanisms. CoRR Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio
2020	J	`jnl`	Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders. CoRR Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis
2020	C	`conf`	KaoKore: A Pre-modern Japanese Art Facial Expression Dataset. ICCC Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto
2020	J	`jnl`	KaoKore: A Pre-modern Japanese Art Facial Expression Dataset. CoRR Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto
2020	J	`jnl`	KuroNet: Regularized Residual U-Nets for End-to-End Kuzushiji Character Recognition. SN Comput. Sci. Alex Lamb, Tarin Clanuwat, Asanobu Kitamoto
2020	A*	`conf`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	J	`jnl`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	J	`jnl`	Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. CoRR Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
2020	J	`jnl`	Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer
2020	A	`conf`	SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. WACV Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
2019	—	`conf`	Adversarial Mixup Resynthesizers. DGS@ICLR Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
2019	J	`jnl`	Adversarial Mixup Resynthesizers. CoRR Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
2019	J	`jnl`	GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. CoRR Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
2019	—	`conf`	Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy. AISec@CCS Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
2019	J	`jnl`	Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy. CoRR Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
2019	J	`jnl`	Interpolation Consistency Training for Semi-Supervised Learning. CoRR Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
2019	A*	`conf`	Interpolation Consistency Training for Semi-supervised Learning. IJCAI Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
2019	A	`conf`	KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning. ICDAR Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto
2019	J	`jnl`	KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning. CoRR Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto
2019	A*	`conf`	Manifold Mixup: Better Representations by Interpolating Hidden States. ICML Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio
2019	A*	`conf`	On Adversarial Mixup Resynthesis. NeurIPS Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal
2019	J	`jnl`	Recurrent Independent Mechanisms. CoRR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2019	J	`jnl`	SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. CoRR Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
2019	A*	`conf`	State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. ICML Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
2019	J	`jnl`	State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer
2018	J	`jnl`	Deep Learning for Classical Japanese Literature. CoRR Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto, David Ha
2018	J	`jnl`	Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations. CoRR Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio
2018	J	`jnl`	Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. CoRR Vikas Verma, Alex Lamb, Christopher Beckham, Aaron C. Courville, Ioannis Mitliagkas, Yoshua Bengio
2017	J	`jnl`	ACtuAL: Actor-Critic Under Adversarial Learning. CoRR Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio
2017	—	`conf`	Adversarially Learned Inference. ICLR (Poster) Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
2017	—	`conf`	GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. NIPS Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
2017	J	`jnl`	GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. CoRR Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Adversarially Learned Inference. CoRR Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
2016	J	`jnl`	Discriminative Regularization for Generative Models. CoRR Alex Lamb, Vincent Dumoulin, Aaron C. Courville
2016	—	`conf`	Professor Forcing: A New Algorithm for Training Recurrent Networks. NIPS Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Professor Forcing: A New Algorithm for Training Recurrent Networks. CoRR Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2015	J	`jnl`	Variance Reduction in SGD by Distributed Importance Sampling. CoRR Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron C. Courville, Yoshua Bengio
2013	—	`conf`	Separating Fact from Fear: Tracking Flu Infections on Twitter. HLT-NAACL Alex Lamb, Michael J. Paul, Mark Dredze
2012	—	`conf`	Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics. AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text Alex Lamb, Michael J. Paul, Mark Dredze