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Online Learning

1012 directly classified papers

Papers per year

Papers

Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NIPS 2024
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts JMLR 2024
Online Classification with Predictions NIPS 2024
Dissimilarity Bandits AISTATS 2024
Faster Recalibration of an Online Predictor via Approachability AISTATS 2024
Fair Online Bilateral Trade NIPS 2024
Maximizing utility in multi-agent environments by anticipating the behavior of other learners NIPS 2024
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries NIPS 2024
Tight Rates for Bandit Control Beyond Quadratics NIPS 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization JMLR 2024
Forgetting, Ignorance or Myopia: Revisiting Key Challenges in Online Continual Learning NIPS 2024
Initializing Services in Interactive ML Systems for Diverse Users NIPS 2024
Real-Time Selection Under General Constraints via Predictive Inference NIPS 2024
Active, anytime-valid risk controlling prediction sets NIPS 2024
Online Consistency of the Nearest Neighbor Rule NIPS 2024
Multiclass Transductive Online Learning NIPS 2024
Improved Analysis for Bandit Learning in Matching Markets NIPS 2024
Binary Search with Distributional Predictions NIPS 2024
Using Surrogates in Covariate-adjusted Response-adaptive Randomization Experiments with Delayed Outcomes NIPS 2024
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice NIPS 2024
How Does Variance Shape the Regret in Contextual Bandits? NIPS 2024
Continuous Prediction with Experts' Advice JMLR 2024
Smoothed Online Classification can be Harder than Batch Classification NIPS 2024
Queueing Matching Bandits with Preference Feedback NIPS 2024
Group-wise oracle-efficient algorithms for online multi-group learning NIPS 2024