Jacob Abernethy
19 papers · 2009–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (11) π Academic Marathon (16)
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Conference Polyglot
(7)
π§
Keyword Pioneer
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Keyword Trendsetter Combo
(4)
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Keyword Champion
(3)
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Century Club
(18)
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Conference Pioneer
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Trend Setter
β
The Questioner
(2)
ποΈ
Keyword Collector
(75)
Conferences
COLT (5)
ICML (4)
ALT (3)
NIPS (3)
ICLR (2)
ACML (1)
JMLR (1)
Top co-authors
Keywords
online learning
(5)
regret minimization
(4)
online linear optimization
(3)
regret bound
(3)
game theory
(2)
adversarial learning
(2)
minimax optimization
(2)
calibrated forecasting
(2)
zero-sum game
(2)
convex optimization
(2)
hedging strategy
(2)
min-max optimization
(2)
learning theory
(2)
nash equilibrium
(1)
low-rank decomposition
(1)
collaborative filtering
(1)
neural network optimization
(1)
online optimization
(1)
sample complexity
(1)
spectral regularization
(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
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
ACML 2021
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization
ALT 2021
Escaping Saddle Points Faster with Stochastic Momentum
ICLR 2020
Conference on Learning Theory 2020: Preface
COLT 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
Minimax Optimal Algorithms for Unconstrained Linear Optimization
NIPS 2013
Large-Scale Bandit Problems and KWIK Learning
ICML 2013
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
NIPS 2013
Adaptive Market Making via Online Learning
NIPS 2013
Does an Efficient Calibrated Forecasting Strategy Exist?
COLT 2011
Blackwell Approachability and No-Regret Learning are Equivalent
COLT 2011
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
JMLR 2009