More from the Same Authors

• 2021 Workshop: Causal Inference & Machine Learning: Why now? »
  Elias Bareinboim · Bernhard Schölkopf · Terrence Sejnowski · Yoshua Bengio · Judea Pearl
• 2021 Poster: Near Optimal Policy Optimization via REPS »
  Aldo Pacchiano · Jonathan N Lee · Peter Bartlett · Ofir Nachum
• 2021 Poster: On the Theory of Reinforcement Learning with Once-per-Episode Feedback »
  Niladri Chatterji · Aldo Pacchiano · Peter Bartlett · Michael Jordan
• 2021 Invited Talk: Benign Overfitting »
  Peter Bartlett
• 2021 Poster: Adversarial Examples in Multi-Layer Random ReLU Networks »
  Peter Bartlett · Sebastien Bubeck · Yeshwanth Cherapanamjeri
• 2020 Poster: Preference learning along multiple criteria: A game-theoretic perspective »
  Kush Bhatia · Ashwin Pananjady · Peter Bartlett · Anca Dragan · Martin Wainwright
• 2020 Poster: Faithful Embeddings for Knowledge Base Queries »
  Haitian Sun · Andrew Arnold · Tania Bedrax Weiss · Fernando Pereira · William Cohen
• 2019 : Poster Session »
  Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar
• 2018 Poster: Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation »
  Kush Bhatia · Aldo Pacchiano · Nicolas Flammarion · Peter Bartlett · Michael Jordan
• 2018 Poster: Horizon-Independent Minimax Linear Regression »
  Alan Malek · Peter Bartlett
• 2018 Poster: Gradient Descent for Spiking Neural Networks »
  Dongsung Huh · Terrence Sejnowski
• 2017 Poster: Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem »
  Yasin Abbasi Yadkori · Peter Bartlett · Victor Gabillon
• 2017 Poster: Spectrally-normalized margin bounds for neural networks »
  Peter Bartlett · Dylan J Foster · Matus Telgarsky
• 2017 Spotlight: Spectrally-normalized margin bounds for neural networks »
  Peter Bartlett · Dylan J Foster · Matus Telgarsky
• 2017 Poster: Alternating minimization for dictionary learning with random initialization »
  Niladri Chatterji · Peter Bartlett
• 2017 Poster: Acceleration and Averaging in Stochastic Descent Dynamics »
  Walid Krichene · Peter Bartlett
• 2017 Spotlight: Acceleration and Averaging in Stochastic Descent Dynamics »
  Walid Krichene · Peter Bartlett
• 2016 : From Brains to Bits and Back Again »
  Yoshua Bengio · Terrence Sejnowski · Christos H Papadimitriou · Jakob H Macke · Demis Hassabis · Alyson Fletcher · Andreas Tolias · Jascha Sohl-Dickstein · Konrad P Koerding
• 2016 Poster: Adaptive Averaging in Accelerated Descent Dynamics »
  Walid Krichene · Alexandre Bayen · Peter Bartlett
• 2015 Poster: Accelerated Mirror Descent in Continuous and Discrete Time »
  Walid Krichene · Alexandre Bayen · Peter Bartlett
• 2015 Spotlight: Accelerated Mirror Descent in Continuous and Discrete Time »
  Walid Krichene · Alexandre Bayen · Peter Bartlett
• 2015 Poster: Minimax Time Series Prediction »
  Wouter Koolen · Alan Malek · Peter Bartlett · Yasin Abbasi Yadkori
• 2014 Workshop: Large-scale reinforcement learning and Markov decision problems »
  Benjamin Van Roy · Mohammad Ghavamzadeh · Peter Bartlett · Yasin Abbasi Yadkori · Ambuj Tewari
• 2014 Poster: Large-Margin Convex Polytope Machine »
  Alex Kantchelian · Michael C Tschantz · Ling Huang · Peter Bartlett · Anthony D Joseph · J. D. Tygar
• 2014 Poster: Efficient Minimax Strategies for Square Loss Games »
  Wouter M Koolen · Alan Malek · Peter Bartlett
• 2013 Workshop: Resource-Efficient Machine Learning »
  Yevgeny Seldin · Yasin Abbasi Yadkori · Yacov Crammer · Ralf Herbrich · Peter Bartlett
• 2013 Poster: How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal »
  Jacob D Abernethy · Peter Bartlett · Rafael Frongillo · Andre Wibisono
• 2013 Spotlight: How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal »
  Jacob D Abernethy · Peter Bartlett · Rafael Frongillo · Andre Wibisono
• 2013 Session: Oral Session 3 »
  Terrence Sejnowski
• 2013 Poster: Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions »
  Yasin Abbasi Yadkori · Peter Bartlett · Varun Kanade · Yevgeny Seldin · Csaba Szepesvari
• 2012 Workshop: Multi-Trade-offs in Machine Learning »
  Yevgeny Seldin · Guy Lever · John Shawe-Taylor · Nicolò Cesa-Bianchi · Yacov Crammer · Francois Laviolette · Gabor Lugosi · Peter Bartlett
• 2012 Invited Talk: Suspicious Coincidences in the Brain »
  Terrence Sejnowski
• 2010 Placeholder: Opening Remarks »
  Terrence Sejnowski · Neil D Lawrence
• 2010 Talk: Opening Remarks and Awards »
  Richard Zemel · Terrence Sejnowski · John Shawe-Taylor
• 2009 Workshop: The Curse of Dimensionality Problem: How Can the Brain Solve It? »
  Simon Haykin · Terrence Sejnowski · Steven W Zucker
• 2009 Poster: Information-theoretic lower bounds on the oracle complexity of convex optimization »
  Alekh Agarwal · Peter Bartlett · Pradeep Ravikumar · Martin J Wainwright
• 2009 Poster: Posterior vs Parameter Sparsity in Latent Variable Models »
  Joao V Graca · Kuzman Ganchev · Ben Taskar · Fernando Pereira
• 2009 Spotlight: Posterior vs Parameter Sparsity in Latent Variable Models »
  Joao V Graca · Kuzman Ganchev · Ben Taskar · Fernando Pereira
• 2009 Spotlight: Information-theoretic lower bounds on the oracle complexity of convex optimization »
  Alekh Agarwal · Peter Bartlett · Pradeep Ravikumar · Martin J Wainwright
• 2009 Poster: Group Sparse Coding »
  Samy Bengio · Fernando Pereira · Yoram Singer · Dennis Strelow
• 2008 Workshop: Cortical Microcircuits and their Computational Functions »
  Tomaso Poggio · Terrence Sejnowski
• 2008 Poster: Exact Convex Confidence-Weighted Learning »
  Yacov Crammer · Mark Dredze · Fernando Pereira
• 2008 Spotlight: Exact Convex Confidence-Weighted Learning »
  Yacov Crammer · Mark Dredze · Fernando Pereira
• 2007 Oral: Adaptive Online Gradient Descent »
  Peter Bartlett · Elad Hazan · Sasha Rakhlin
• 2007 Poster: Adaptive Online Gradient Descent »
  Peter Bartlett · Elad Hazan · Sasha Rakhlin
• 2007 Spotlight: Structured Learning with Approximate Inference »
  Alex Kulesza · Fernando Pereira
• 2007 Poster: Structured Learning with Approximate Inference »
  Alex Kulesza · Fernando Pereira
• 2007 Poster: Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs »
  Ambuj Tewari · Peter Bartlett
• 2007 Poster: Learning Bounds for Domain Adaptation »
  John Blitzer · Yacov Crammer · Alex Kulesza · Fernando Pereira · Jennifer Wortman Vaughan
• 2006 Workshop: Decoding the neural code »
  Eric Thomson · Bill Kristan · Terrence Sejnowski
• 2006 Poster: Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds »
  Benjamin Rubinstein · Peter Bartlett · J. Hyam Rubinstein
• 2006 Poster: Sample Complexity of Policy Search with Known Dynamics »
  Peter Bartlett · Ambuj Tewari
• 2006 Poster: Analysis of Representations for Domain Adaptation »
  John Blitzer · Shai Ben-David · Yacov Crammer · Fernando Pereira
• 2006 Poster: AdaBoost is Consistent »
  Peter Bartlett · Mikhail Traskin