A heuristic routing mechanism using a new addressing scheme. - Mohsen Ravanbakhsh; Yasin Abbasi-Yadkori; Maghsoud Abbaspour; Hamid Sarbazi-Azad (BIONETICS, 2006)

Learning when to stop thinking and do something! - Barnabás Póczos; Yasin Abbasi-Yadkori; Csaba Szepesvári; Russell Greiner; Nathan R. Sturtevant (ICML, 2009)

Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling. - Peter Hooper; Yasin Abbasi-Yadkori; Russell Greiner; Bret Hoehn (UAI, 2009)

Extending rapidly-exploring random trees for asymptotically optimal anytime motion planning. - Yasin Abbasi-Yadkori; Joseph Modayil; Csaba Szepesvári (IROS, 2010)

Fast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph. - Kiana Hajebi; Yasin Abbasi-Yadkori; Hossein Shahbazi; Hong Zhang 013 (IJCAI, 2011)

Improved Algorithms for Linear Stochastic Bandits. - Yasin Abbasi-Yadkori; Dávid Pál; Csaba Szepesvári (NIPS, 2011)

Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems - Yasin Abbasi-Yadkori; Dávid Pál; Csaba Szepesvári (CoRR, 2011)

Regret Bounds for the Adaptive Control of Linear Quadratic Systems. - Yasin Abbasi-Yadkori; Csaba Szepesvári (COLT, 2011)

Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments. - Yevgeny Seldin; Csaba Szepesvári; Peter Auer; Yasin Abbasi-Yadkori (EWRL, 2012)

Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits. - Yasin Abbasi-Yadkori; Dávid Pál; Csaba Szepesvári (AISTATS, 2012)

Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Varun Kanade; Yevgeny Seldin; Csaba Szepesvári (NIPS, 2013)

Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions - Yasin Abbasi-Yadkori; Peter L. Bartlett; Csaba Szepesvári (CoRR, 2013)

Tracking Adversarial Targets. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Varun Kanade (ICML, 2014)

Linear Programming for Large-Scale Markov Decision Problems. - Alan Malek; Yasin Abbasi-Yadkori; Peter L. Bartlett (ICML, 2014)

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations. - Yevgeny Seldin; Peter L. Bartlett; Koby Crammer; Yasin Abbasi-Yadkori (ICML, 2014)

Online learning in MDPs with side information. - Yasin Abbasi-Yadkori; Gergely Neu (CoRR, 2014)

Bayesian Optimal Control of Smoothly Parameterized Systems: The Lazy Posterior Sampling Algorithm. - Yasin Abbasi-Yadkori; Csaba Szepesvári (CoRR, 2014)

Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Xi Chen 022; Alan Malek (ICML, 2015)

Minimax Time Series Prediction. - Wouter M. Koolen; Alan Malek; Peter L. Bartlett; Yasin Abbasi-Yadkori (NIPS, 2015)

Bayesian Optimal Control of Smoothly Parameterized Systems. - Yasin Abbasi-Yadkori; Csaba Szepesvári (UAI, 2015)

A Fast and Reliable Policy Improvement Algorithm. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Stephen J. Wright 001 (AISTATS, 2016)

Hit-and-Run for Sampling and Planning in Non-Convex Spaces. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Victor Gabillon; Alan Malek (AISTATS, 2017)

Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Victor Gabillon (NIPS, 2017)

Conservative Contextual Linear Bandits. - Abbas Kazerouni; Mohammad Ghavamzadeh; Yasin Abbasi; Benjamin Van Roy (NIPS, 2017)

Posterior Sampling for Large Scale Reinforcement Learning. - Georgios Theocharous; Zheng Wen 002; Yasin Abbasi-Yadkori; Nikos Vlassis (CoRR, 2017)

Stochastic Low-Rank Bandits. - Branislav Kveton; Csaba Szepesvári; Anup Rao 002; Zheng Wen 002; Yasin Abbasi-Yadkori; S. Muthukrishnan 001 (CoRR, 2017)

Best of both worlds: Stochastic & adversarial best-arm identification. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Victor Gabillon; Alan Malek; Michal Valko (COLT, 2018)

Offline Evaluation of Ranking Policies with Click Models. - Shuai Li 010; Yasin Abbasi-Yadkori; Branislav Kveton; S. Muthukrishnan 001; Vishwa Vinay; Zheng Wen 002 (KDD, 2018)

Scalar Posterior Sampling with Applications. - Georgios Theocharous; Zheng Wen 002; Yasin Abbasi; Nikos Vlassis (NeurIPS, 2018)

A Continuation Method for Discrete Optimization and its Application to Nearest Neighbor Classification. - Ali Shameli; Yasin Abbasi-Yadkori (CoRR, 2018)

Optimizing over a Restricted Policy Class in Markov Decision Processes. - Ershad Banijamali; Yasin Abbasi-Yadkori; Mohammad Ghavamzadeh; Nikos Vlassis (CoRR, 2018)

Regret Bounds for Model-Free Linear Quadratic Control. - Yasin Abbasi-Yadkori; Nevena Lazic; Csaba Szepesvári (CoRR, 2018)

Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting. - Xiang Cheng 006; Niladri S. Chatterji; Yasin Abbasi-Yadkori; Peter L. Bartlett; Michael I. Jordan (CoRR, 2018)

New Insights into Bootstrapping for Bandits. - Sharan Vaswani; Branislav Kveton; Zheng Wen 002; Anup Rao 002; Mark Schmidt 001; Yasin Abbasi-Yadkori (CoRR, 2018)

Model-Free Linear Quadratic Control via Reduction to Expert Prediction. - Yasin Abbasi-Yadkori; Nevena Lazic; Csaba Szepesvári (AISTATS, 2019)

Optimizing over a Restricted Policy Class in MDPs. - Ershad Banijamali; Yasin Abbasi-Yadkori; Mohammad Ghavamzadeh; Nikos Vlassis (AISTATS, 2019)

Sample Efficient Graph-Based Optimization with Noisy Observations. - Thanh Tan Nguyen; Ali Shameli; Yasin Abbasi-Yadkori; Anup Rao 002; Branislav Kveton (AISTATS, 2019)

Bootstrapping Upper Confidence Bound. - Botao Hao; Yasin Abbasi-Yadkori; Zheng Wen 002; Guang Cheng 003 (NeurIPS, 2019)

Thompson Sampling and Approximate Inference. - My Phan; Yasin Abbasi-Yadkori; Justin Domke (NeurIPS, 2019)

On Densification for Minwise Hashing. - Tung Mai; Anup Rao 002; Matt Kapilevich; Ryan A. Rossi; Yasin Abbasi-Yadkori; Ritwik Sinha (UAI, 2019)

Large-Scale Markov Decision Problems via the Linear Programming Dual. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Xi Chen 010; Alan Malek (CoRR, 2019)

Exploration-Enhanced POLITEX. - Yasin Abbasi-Yadkori; Nevena Lazic; Csaba Szepesvári; Gellért Weisz (CoRR, 2019)

Model Selection in Contextual Stochastic Bandit Problems. - Aldo Pacchiano; My Phan; Yasin Abbasi-Yadkori; Anup Rao 002; Julian Zimmert; Tor Lattimore; Csaba Szepesvári (NeurIPS, 2020)

A Structural Graph Representation Learning Framework. - Ryan A. Rossi; Nesreen K. Ahmed; Eunyee Koh; Sungchul Kim; Anup Rao 002; Yasin Abbasi-Yadkori (WSDM, 2020)

Provably Efficient Adaptive Approximate Policy Iteration. - Botao Hao; Nevena Lazic; Yasin Abbasi-Yadkori; Pooria Joulani; Csaba Szepesvári (CoRR, 2020)

Regret Balancing for Bandit and RL Model Selection. - Yasin Abbasi-Yadkori; Aldo Pacchiano; My Phan (CoRR, 2020)

The Elliptical Potential Lemma Revisited. - Alexandra Carpentier; Claire Vernade; Yasin Abbasi-Yadkori (CoRR, 2020)

Adaptive Approximate Policy Iteration. - Botao Hao; Nevena Lazic; Yasin Abbasi-Yadkori; Pooria Joulani; Csaba Szepesvári (AISTATS, 2021)

On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function. - Gellért Weisz; Philip Amortila; Barnabás Janzer; Yasin Abbasi-Yadkori; Nan Jiang 008; Csaba Szepesvári (COLT, 2021)

Improved Regret Bound and Experience Replay in Regularized Policy Iteration. - Nevena Lazic; Dong Yin; Yasin Abbasi-Yadkori; Csaba Szepesvári (ICML, 2021)

Optimization Issues in KL-Constrained Approximate Policy Iteration. - Nevena Lazic; Botao Hao; Yasin Abbasi-Yadkori; Dale Schuurmans; Csaba Szepesvári (CoRR, 2021)

Parameter and Feature Selection in Stochastic Linear Bandits. - Ahmadreza Moradipari; Yasin Abbasi-Yadkori; Mahnoosh Alizadeh; Mohammad Ghavamzadeh (CoRR, 2021)

Confident Least Square Value Iteration with Local Access to a Simulator. - Botao Hao; Nevena Lazic; Dong Yin; Yasin Abbasi-Yadkori; Csaba Szepesvári (AISTATS, 2022)

Efficient local planning with linear function approximation. - Dong Yin; Botao Hao; Yasin Abbasi-Yadkori; Nevena Lazic; Csaba Szepesvári (ALT, 2022)

Feature and Parameter Selection in Stochastic Linear Bandits. - Ahmadreza Moradipari; Berkay Turan; Yasin Abbasi-Yadkori; Mahnoosh Alizadeh; Mohammad Ghavamzadeh (ICML, 2022)

Context-lumpable stochastic bandits. - Chung-Wei Lee; Qinghua Liu; Yasin Abbasi-Yadkori; Chi Jin 001; Tor Lattimore; Csaba Szepesvári (NeurIPS, 2023)

A New Look at Dynamic Regret for Non-Stationary Stochastic Bandits. - Yasin Abbasi-Yadkori; András György 001; Nevena Lazic (J. Mach. Learn. Res., 2023)

To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; András György 001; Csaba Szepesvári (NeurIPS, 2024)

Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Arms. - Mohammad Javad Azizi; Thang Duong; Yasin Abbasi-Yadkori; András György 001; Claire Vernade; Mohammad Ghavamzadeh (RLJ, 2024)

Mitigating LLM Hallucinations via Conformal Abstention. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; David Stutz; András György 001; Adam Fisch; Arnaud Doucet; Iuliya Beloshapka; Wei-Hung Weng; Yao-Yuan Yang; Csaba Szepesvári; Ali Taylan Cemgil; Nenad Tomasev (CoRR, 2024)

To Believe or Not to Believe Your LLM. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; András György 001; Csaba Szepesvári (CoRR, 2024)

Low-rank bias, weight decay, and model merging in neural networks. - Ilja Kuzborskij; Yasin Abbasi-Yadkori (CoRR, 2025)

Pointwise confidence estimation in the non-linear ℓ2-regularized least squares. - Ilja Kuzborskij; Yasin Abbasi-Yadkori (CoRR, 2025)

Hierarchical Reasoning Model. - Guan Wang; Jin Li; Yuhao Sun; Xing Chen; Changling Liu; Yue Wu; Meng Lu; Sen Song; Yasin Abbasi-Yadkori (CoRR, 2025)