Jacob Abernethy
19 papers · 2009–2026 · 7 venues · across top CS/AI venues
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Achievements
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(12)
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Keyword Pioneer
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(2)
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Research topics
Machine Learning
(18)
Optimization & Theory
(17)
Mathematics & Optimization
(9)
Optimization
(9)
Artificial Intelligence
(8)
Core AI
(7)
Learning Types
(7)
Deep Learning
(2)
Probability
(2)
Knowledge & Reasoning
(1)
Natural Language Processing
(1)
Architectures
(1)
Core Methods
(1)
Learning Paradigms
(1)
Mathematics
(1)
Keywords
online learning
(7)
regret minimization
(4)
regret bound
(3)
online linear optimization
(3)
adversarial learning
(2)
convex optimization
(2)
minimax optimization
(2)
min-max optimization
(2)
hedging strategy
(2)
zero-sum game
(2)
game theory
(2)
learning theory
(2)
calibrated forecasting
(2)
transformer
(1)
minimax optimality
(1)
sample complexity
(1)
convergence analysis
(1)
non-convex optimization
(1)
stochastic gradient descent
(1)
supervised learning
(1)
Papers
Multi-distribution Learning: From Worst-Case Optimality to Lexicographic Min-Max Optimality
ALT 2026
Can Transformers Reason Logically? A Study in SAT Solving
ICML 2025
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks
ALT 2024
On Accelerated Perceptrons and Beyond
ICLR 2023
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization
ALT 2021
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
ACML 2021
Conference on Learning Theory 2020: Preface
COLT 2020
Escaping Saddle Points Faster with Stochastic Momentum
ICLR 2020
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
ICML 2019
Faster Rates for Convex-Concave Games
COLT 2018
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier
ICML 2016
Online Linear Optimization via Smoothing
COLT 2014
Adaptive Market Making via Online Learning
NeurIPS 2013
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
NeurIPS 2013
Large-Scale Bandit Problems and KWIK Learning
ICML 2013
Minimax Optimal Algorithms for Unconstrained Linear Optimization
NeurIPS 2013
Blackwell Approachability and No-Regret Learning are Equivalent
COLT 2011
Does an Efficient Calibrated Forecasting Strategy Exist?
COLT 2011
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
JMLR 2009