Co-occurring keywords · papers mentioning both
Papers
Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization
COLT 2026
Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret
COLT 2026
Adversarially Robust Multitask Adaptive Control
L4DC 2026
Almost sure null bankruptcy of testing-by-betting strategies
COLT 2026
A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses
AAAI 2026
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design
JMLR 2026
A simple, optimal and efficient algorithm for online exp-concave optimization
COLT 2026
A Symplectic Analysis of Alternating Mirror Descent
JMLR 2026
A Tight Lower Bound for Non-stochastic Multi-armed Bandits with Expert Advice
COLT 2026
Avoiding exp($k^*$) Scaling for Thompson Sampling in Combinatorial Semi-Bandits: From Multiple Seeds to a Single Seed
COLT 2026
Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization
UAI 2026
Bandit Learning for Online Scheduling with Immediate Decision
UAI 2026
Bootstrapping LLMs via Preference-Based Policy Optimization
AAAI 2026
Characterizing Online and Private Learnability under Distributional Constraints via Generalized Smoothness
COLT 2026
Clipping the Price of Adaptivity at the Tail
COLT 2026
Constrained Online Convex Optimization with Memory and Predictions
AAAI 2026
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
UAI 2026
Decentralized Online Convex Optimization with Unknown Feedback Delays
AAAI 2026
Distributionally Robust Online Markov Game with Linear Function Approximation
AAAI 2026
Distribution-Dependent Rates for Multi-Distribution Learning
ALT 2026
Dynamic Regret in Outlier-Oblivious Online Optimization using Nonconvex Robust Losses
UAI 2026
ECPv2: Fast, Efficient, and Scalable Global Optimization of Lipschitz Functions
AAAI 2026
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
ALT 2026
Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
ALT 2026
Exploiting Concavity Information in Contextual Bandit Optimization
UAI 2026