Reichman, Daniel

12 publications

COLT 2025 Depth Separations in Neural Networks: Separating the Dimension from the Accuracy Itay Safran, Daniel Reichman, Paul Valiant

NeurIPS 2025 Protocols for Verifying Smooth Strategies in Bandits and Games Miranda Christ, Daniel Reichman, Jonathan Shafer

NeurIPS 2025 The Computational Complexity of Counting Linear Regions in ReLU Neural Networks Moritz Stargalla, Christoph Hertrich, Daniel Reichman

NeurIPSW 2024 Predicting Human Decisions with Behavioral Theories and Machine Learning Ori Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart Russell, Evan Carter, James F. Cavanagh, Ido Erev

NeurIPSW 2024 The Karp Dataset Mason DiCicco, Eamon Worden, Daniel Reichman, Neil Heffernan, Conner Olsen, Nikhil Gangaram

NeurIPS 2022 Size and Depth of Monotone Neural Networks: Interpolation and Approximation Dan Mikulincer, Daniel Reichman

COLT 2021 Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi, Daniel Reichman, Toniann Pitassi, Ohad Shamir

ICML 2019 Cognitive Model Priors for Predicting Human Decisions David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Stuart J. Russell, Thomas L. Griffiths

AISTATS 2018 Inference in Sparse Graphs with Pairwise Measurements and Side Information Dylan J. Foster, Karthik Sridharan, Daniel Reichman

NeurIPS 2017 A Graph-Theoretic Approach to Multitasking Noga Alon, Daniel Reichman, Igor Shinkar, Tal Wagner, Sebastian Musslick, Jonathan D. Cohen, Tom Griffiths, Biswadip Dey, Kayhan Ozcimder

NeurIPS 2015 On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors Andrea Montanari, Daniel Reichman, Ofer Zeitouni

CVPR 2013 FasT-Match: Fast Affine Template Matching Simon Korman, Daniel Reichman, Gilad Tsur, Shai Avidan