Abernethy, Jacob

19 publications

ICML 2025 Can Transformers Reason Logically? a Study in SAT Solving Leyan Pan, Vijay Ganesh, Jacob Abernethy, Chris Esposo, Wenke Lee

ALT 2024 A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks Jacob Abernethy, Alekh Agarwal, Teodor Vanislavov Marinov, Manfred K. Warmuth

ICLR 2023 On Accelerated Perceptrons and Beyond Guanghui Wang, Rafael Hanashiro, Etash Kumar Guha, Jacob Abernethy

ICMLW 2023 Randomized Quantization Is All You Need for Differential Privacy in Federated Learning Yeojoon Youn, Zihao Hu, Juba Ziani, Jacob Abernethy

NeurIPSW 2022 Accelerated Federated Optimization with Quantization Yeojoon Youn, Bhuvesh Kumar, Jacob Abernethy

ALT 2021 Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization Jacob Abernethy, Kevin A. Lai, Andre Wibisono

ACML 2021 Understanding How Over-Parametrization Leads to Acceleration: A Case of Learning a Single Teacher Neuron Jun-Kun Wang, Jacob Abernethy

COLT 2020 Conference on Learning Theory 2020: Preface Jacob Abernethy, Shivani Agarwal

ICLR 2020 Escaping Saddle Points Faster with Stochastic Momentum Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy

ICLR 2020 Last-Iterate Convergence Rates for Min-Max Optimization Jacob Abernethy, Kevin A. Lai, Andre Wibisono

ICML 2019 Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games Adrian Rivera Cardoso, Jacob Abernethy, He Wang, Huan Xu

ICML 2016 Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier Jacob Abernethy, Elad Hazan

NeurIPS 2013 Adaptive Market Making via Online Learning Jacob Abernethy, Satyen Kale

NeurIPS 2013 How to Hedge an Option Against an Adversary: Black-Scholes Pricing Is Minimax Optimal Jacob Abernethy, Peter L Bartlett, Rafael Frongillo, Andre Wibisono

ICML 2013 Large-Scale Bandit Problems and KWIK Learning Jacob Abernethy, Kareem Amin, Michael Kearns, Moez Draief

NeurIPS 2013 Minimax Optimal Algorithms for Unconstrained Linear Optimization Brendan McMahan, Jacob Abernethy

COLT 2011 Blackwell Approachability and No-Regret Learning Are Equivalent Jacob Abernethy, Peter L. Bartlett, Elad Hazan

COLT 2011 Does an Efficient Calibrated Forecasting Strategy Exist? Jacob Abernethy, Shie Mannor

JMLR 2009 A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert