Jimmy Ba - RankMe

107 papers A* 35A 2Journal 55Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	EMA Policy Gradient: Taming Reinforcement Learning for LLMs with EMA Anchor and Top-k KL. CoRR Lunjun Zhang, Jimmy Ba
2025	J	`jnl`	Mastering diverse control tasks through world models. Nat. Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy P. Lillicrap
2024	J	`jnl`	Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2024	A*	`conf`	Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
2024	A*	`conf`	OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. ICLR Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba
2024	J	`jnl`	Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. CoRR Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang
2024	J	`jnl`	The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. CoRR Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D. Li, Ann-Kathrin Dombrowski, Shashwat Goel, Long Phan, Gabriel Mukobi, Nathan Helm-Burger, Rassin Lababidi, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Adam Khoja, Zhenqi Zhao, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Liu, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Russell Kaplan, Ian Steneker, David Campbell, Brad Jokubaitis, Alex Levinson, Jean Wang, William Qian, Kallol Krishna Karmakar, Steven Basart, Stephen Fitz, Mindy Levine, Ponnurangam Kumaraguru, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks
2024	A*	`conf`	The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning. ICML Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D. Li, Ann-Kathrin Dombrowski, Shashwat Goel, Gabriel Mukobi, Nathan Helm-Burger, Rassin Lababidi, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Lin, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Ian Steneker, David Campbell, Brad Jokubaitis, Steven Basart, Stephen Fitz, Ponnurangam Kumaraguru, Kallol Krishna Karmakar, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks
2023	A*	`conf`	AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
2023	J	`jnl`	AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
2023	J	`jnl`	Boosted Prompt Ensembles for Large Language Models. CoRR Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba
2023	—	`conf`	Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2023	J	`jnl`	Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding. CoRR Augustin Toma, Patrick R. Lawler, Jimmy Ba, Rahul G. Krishnan, Barry B. Rubin, Bo Wang
2023	—	`conf`	Decomposed Prompting to Answer Questions on a Course Discussion Board. AIED (Posters/Late Breaking Results/...) Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
2023	J	`jnl`	Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
2023	A*	`conf`	Large Language Models are Human-Level Prompt Engineers. ICLR Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
2023	A*	`conf`	Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective. NeurIPS Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu
2023	J	`jnl`	Mastering Diverse Domains through World Models. CoRR Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy P. Lillicrap
2023	A*	`conf`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse
2023	J	`jnl`	OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. CoRR Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba
2023	J	`jnl`	Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization. CoRR Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Jimmy Ba, Amjad Almahairi
2023	—	`conf`	Residual Prompt Tuning: improving prompt tuning with residual reparameterization. ACL (Findings) Anastasia Razdaibiedina, Yuning Mao, Madian Khabsa, Mike Lewis, Rui Hou, Jimmy Ba, Amjad Almahairi
2023	A*	`conf`	STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. NeurIPS Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
2023	J	`jnl`	STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. CoRR Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
2023	A*	`conf`	TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. ICML Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem
2023	J	`jnl`	TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. CoRR Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem
2023	J	`jnl`	Training on Thin Air: Improve Image Classification with Generated Data. CoRR Yongchao Zhou, Hshmat Sahak, Jimmy Ba
2023	J	`jnl`	Using Large Language Models for Hyperparameter Optimization. CoRR Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba
2022	A*	`conf`	Dataset Distillation using Neural Feature Regression. NeurIPS Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
2022	J	`jnl`	Dataset Distillation using Neural Feature Regression. CoRR Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
2022	J	`jnl`	Exploring Low Rank Training of Deep Neural Networks. CoRR Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez
2022	A*	`conf`	High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. NeurIPS Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
2022	J	`jnl`	High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. CoRR Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
2022	J	`jnl`	Large Language Models Are Human-Level Prompt Engineers. CoRR Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
2022	J	`jnl`	Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse
2022	A*	`conf`	Understanding the Variance Collapse of SVGD in High Dimensions. ICLR Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang
2022	J	`jnl`	You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. CoRR Keiran Paster, Sheila A. McIlraith, Jimmy Ba
2022	A*	`conf`	You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. NeurIPS Keiran Paster, Sheila A. McIlraith, Jimmy Ba
2021	A*	`conf`	Clockwork Variational Autoencoders. NeurIPS Vaibhav Saxena, Jimmy Ba, Danijar Hafner
2021	J	`jnl`	Clockwork Variational Autoencoders. CoRR Vaibhav Saxena, Jimmy Ba, Danijar Hafner
2021	A*	`conf`	Efficient Statistical Tests: A Neural Tangent Kernel Approach. ICML Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba
2021	A*	`conf`	How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? NeurIPS Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba
2021	A*	`conf`	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. ICLR Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger Baker Grosse
2021	A*	`conf`	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. ICML Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
2021	J	`jnl`	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. CoRR Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
2021	A*	`conf`	Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
2021	J	`jnl`	Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
2021	A*	`conf`	Mastering Atari with Discrete World Models. ICLR Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba
2021	A*	`conf`	Planning from Pixels using Inverse Dynamics Models. ICLR Keiran Paster, Sheila A. McIlraith, Jimmy Ba
2021	A*	`conf`	When does preconditioning help or hurt generalization? ICLR Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
2020	J	`jnl`	A Study of Gradient Variance in Deep Learning. CoRR Fartash Faghri, David Duvenaud, David J. Fleet, Jimmy Ba
2020	J	`jnl`	Action and Perception as Divergence Minimization. CoRR Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl J. Friston, Nicolas Heess
2020	A	`conf`	An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2020	A*	`conf`	An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. ICLR Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba
2020	J	`jnl`	An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. CoRR Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba
2020	J	`jnl`	BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. CoRR Yeming Wen, Dustin Tran, Jimmy Ba
2020	A*	`conf`	BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. ICLR Yeming Wen, Dustin Tran, Jimmy Ba
2020	A*	`conf`	Dream to Control: Learning Behaviors by Latent Imagination. ICLR Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi
2020	J	`jnl`	Evaluating Agents without Rewards. CoRR Brendon Matusch, Jimmy Ba, Danijar Hafner
2020	A*	`conf`	Exploring Model-based Planning with Policy Networks. ICLR Tingwu Wang, Jimmy Ba
2020	A*	`conf`	Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint. ICLR Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang
2020	J	`jnl`	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. CoRR Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger B. Grosse
2020	A*	`conf`	Improving Transformer Optimization Through Better Initialization. ICML Xiao Shi Huang, Felipe Pérez, Jimmy Ba, Maksims Volkovs
2020	A	`conf`	Learning Intrinsic Rewards as a Bi-Level Optimization Problem. UAI Bradly C. Stadie, Lunjun Zhang, Jimmy Ba
2020	J	`jnl`	Mastering Atari with Discrete World Models. CoRR Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba
2020	A*	`conf`	Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. ICML Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
2020	J	`jnl`	Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. CoRR Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
2020	J	`jnl`	Noisy Labels Can Induce Good Representations. CoRR Jingling Li, Mozhi Zhang, Keyulu Xu, John P. Dickerson, Jimmy Ba
2020	A*	`conf`	On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. ICLR Yuanhao Wang, Guodong Zhang, Jimmy Ba
2020	J	`jnl`	Planning from Pixels using Inverse Dynamics Models. CoRR Keiran Paster, Sheila A. McIlraith, Jimmy Ba
2020	J	`jnl`	The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning. CoRR Yuhuai Wu, Honghua Dong, Roger B. Grosse, Jimmy Ba
2020	J	`jnl`	When Does Preconditioning Help or Hurt Generalization? CoRR Shun-ichi Amari, Jimmy Ba, Roger B. Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
2019	J	`jnl`	ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning. CoRR Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba
2019	J	`jnl`	Benchmarking Model-Based Reinforcement Learning. CoRR Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric D. Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba
2019	—	`conf`	DOM-Q-NET: Grounded RL on Structured Language. ICLR (Poster) Sheng Jia, Jamie Kiros, Jimmy Ba
2019	J	`jnl`	DOM-Q-NET: Grounded RL on Structured Language. CoRR Sheng Jia, Jamie Kiros, Jimmy Ba
2019	J	`jnl`	Dream to Control: Learning Behaviors by Latent Imagination. CoRR Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi
2019	J	`jnl`	Exploring Model-based Planning with Policy Networks. CoRR Tingwu Wang, Jimmy Ba
2019	A*	`conf`	Graph Normalizing Flows. NeurIPS Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky
2019	J	`jnl`	Graph Normalizing Flows. CoRR Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky
2019	J	`jnl`	Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
2019	A*	`conf`	Lookahead Optimizer: k steps forward, 1 step back. NeurIPS Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
2019	J	`jnl`	Lookahead Optimizer: k steps forward, 1 step back. CoRR Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba
2019	—	`conf`	Neural Graph Evolution: Towards Efficient Automatic Robot Design. ICLR (Poster) Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba
2019	J	`jnl`	Neural Graph Evolution: Towards Efficient Automatic Robot Design. CoRR Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba
2019	J	`jnl`	On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. CoRR Yuanhao Wang, Guodong Zhang, Jimmy Ba
2018	—	`conf`	Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
2018	J	`jnl`	Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
2018	—	`conf`	Kronecker-factored Curvature Approximations for Recurrent Neural Networks. ICLR (Poster) James Martens, Jimmy Ba, Matt Johnson
2018	—	`conf`	NerveNet: Learning Structured Policy with Graph Neural Networks. ICLR (Poster) Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler
2018	A*	`conf`	On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
2018	A*	`conf`	Reversible Recurrent Neural Networks. NeurIPS Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse
2018	J	`jnl`	Reversible Recurrent Neural Networks. CoRR Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse
2018	J	`jnl`	Solving Approximate Wasserstein GANs to Stationarity. CoRR Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
2017	—	`conf`	Distributed Second-Order Optimization using Kronecker-Factored Approximations. ICLR (Poster) Jimmy Ba, Roger B. Grosse, James Martens
2017	—	`conf`	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba
2017	J	`jnl`	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation. CoRR Yuhuai Wu, Elman Mansimov, Shun Liao, Roger B. Grosse, Jimmy Ba
2016	—	`conf`	Using Fast Weights to Attend to the Recent Past. NIPS Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2016	J	`jnl`	Using Fast Weights to Attend to the Recent Past. CoRR Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
2015	—	`conf`	Adam: A Method for Stochastic Optimization. ICLR (Poster) Diederik P. Kingma, Jimmy Ba
2015	—	`conf`	Learning Wake-Sleep Recurrent Attention Models. NIPS Jimmy Ba, Ruslan Salakhutdinov, Roger B. Grosse, Brendan J. Frey
2015	J	`jnl`	Learning Wake-Sleep Recurrent Attention Models. CoRR Jimmy Ba, Roger B. Grosse, Ruslan Salakhutdinov, Brendan J. Frey
2015	—	`conf`	Multiple Object Recognition with Visual Attention. ICLR (Poster) Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu
2015	J	`jnl`	Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptions. CoRR Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov
2015	A*	`conf`	Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. ICML Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio
2015	J	`jnl`	Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio
2014	—	`conf`	Do Deep Nets Really Need to be Deep? NIPS Jimmy Ba, Rich Caruana