2024 "online learning" Papers
32 papers found
Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search
Thomy Phan, Taoan Huang, Bistra Dilkina et al.
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.
Adaptive Robust Learning using Latent Bernoulli Variables
Aleksandr Karakulev, Dave Zachariah, Prashant Singh
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotlowski, Marek Wydmuch, Erik Schultheis et al.
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
Yanfei Zhou, Lars Lindemann, Matteo Sesia
Designing Decision Support Systems using Counterfactual Prediction Sets
Eleni Straitouri, Manuel Gomez-Rodriguez
Doubly Perturbed Task Free Continual Learning
Byung Hyun Lee, Min-hwan Oh, Se Young Chun
Efficient Learning in Polyhedral Games via Best-Response Oracles
Darshan Chakrabarti, Gabriele Farina, Christian Kroer
Efficient Online Set-valued Classification with Bandit Feedback
Zhou Wang, Xingye Qiao
Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing
Ioannis Maniadis Metaxas, Georgios Tzimiropoulos, ioannis Patras
Factored-Reward Bandits with Intermediate Observations
Marco Mussi, Simone Drago, Marcello Restelli et al.
Federated Combinatorial Multi-Agent Multi-Armed Bandits
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
Graph2Tac: Online Representation Learning of Formal Math Concepts
Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.
High-dimensional Linear Bandits with Knapsacks
Wanteng Ma, Dong Xia, Jiashuo Jiang
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Luca Viano, EFSTRATIOS PANTELEIMON SKOULAKIS, Volkan Cevher
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
Wang Chi Cheung, Lixing Lyu
Monotone Individual Fairness
Yahav Bechavod
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
Kwang-Sung Jun, Jungtaek Kim
Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement
Fushuo Huo, Wenchao Xu, Jingcai Guo et al.
Online Cascade Learning for Efficient Inference over Streams
Lunyiu Nie, Zhimin Ding, Erdong Hu et al.
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer et al.
Online Learning in Betting Markets: Profit versus Prediction
Haiqing Zhu, Alexander Soen, Yun Kuen Cheung et al.
Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints
Francesco Emanuele Stradi, Jacopo Germano, Gianmarco Genalti et al.
Online Learning under Budget and ROI Constraints via Weak Adaptivity
Matteo Castiglioni, Andrea Celli, Christian Kroer
Online Learning with Bounded Recall
Jon Schneider, Kiran Vodrahalli
Online Matrix Completion: A Collaborative Approach with Hott Items
Dheeraj Baby, Soumyabrata Pal
Online Variational Sequential Monte Carlo
Alessandro Mastrototaro, Jimmy Olsson
Parameterized Projected Bellman Operator
Théo Vincent, Alberto Maria Metelli, Boris Belousov et al.
Performative Prediction with Bandit Feedback: Learning through Reparameterization
Yatong Chen, Wei Tang, Chien-Ju Ho et al.
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook et al.