A Sampling-Based Approach to Reducing the Complexity of Continuous State Space POMDPs by Decomposition Into Coupled Perceptual and Decision Processes. - Rasool Fakoor; Manfred Huber (ICMLA (1), 2012)

An integrated cloud-based framework for mobile phone sensing. - Rasool Fakoor; Mayank Raj; Azade Nazi; Mario Di Francesco; Sajal K. Das 001 (MCC@SIGCOMM, 2012)

Improving tractability of POMDPs by separation of decision and perceptual processes. - Rasool Fakoor; Manfred Huber (SMC, 2012)

Memory-augmented Attention Modelling for Videos. - Rasool Fakoor; Abdel-rahman Mohamed; Margaret Mitchell; Sing Bing Kang; Pushmeet Kohli (CoRR, 2016)

Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality. - Rasool Fakoor; Xiaodong He 001; Ivan Tashev; Shuayb Zarar (CoRR, 2017)

Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy. - Rasool Fakoor; Xiaodong He 001; Ivan Tashev; Shuayb Zarar (ICASSP, 2018)

Direct Optimization of F-Measure for Retrieval-Based Personal Question Answering. - Rasool Fakoor; Amanjit Kainth; Siamak Shakeri; Christopher Winestock; Abdel-rahman Mohamed; Ruhi Sarikaya (SLT, 2018)

Differentiable Greedy Networks. - Thomas Powers; Rasool Fakoor; Siamak Shakeri; Abhinav Sethy; Amanjit Kainth; Abdel-rahman Mohamed; Ruhi Sarikaya (CoRR, 2018)

P3O: Policy-on Policy-off Policy Optimization. - Rasool Fakoor; Pratik Chaudhari; Alexander J. Smola (UAI, 2019)

Meta-Q-Learning. - Rasool Fakoor; Pratik Chaudhari; Stefano Soatto; Alexander J. Smola (ICLR, 2020)

Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. - Rasool Fakoor; Jonas Mueller 001; Nick Erickson; Pratik Chaudhari; Alexander J. Smola (NeurIPS, 2020)

TraDE: Transformers for Density Estimation. - Rasool Fakoor; Pratik Chaudhari; Jonas Mueller 001; Alexander J. Smola (CoRR, 2020)

DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. - Rasool Fakoor; Pratik Chaudhari; Alexander J. Smola (CoRR, 2020)

Continuous Doubly Constrained Batch Reinforcement Learning. - Rasool Fakoor; Jonas Mueller 001; Kavosh Asadi; Pratik Chaudhari; Alexander J. Smola (NeurIPS, 2021)

Continuous Doubly Constrained Batch Reinforcement Learning. - Rasool Fakoor; Jonas Mueller 001; Pratik Chaudhari; Alexander J. Smola (CoRR, 2021)

Deep Quantile Aggregation. - Taesup Kim; Rasool Fakoor; Jonas Mueller 001; Alexander J. Smola; Ryan J. Tibshirani (CoRR, 2021)

Deep Q-Network with Proximal Iteration. - Kavosh Asadi; Rasool Fakoor; Omer Gottesman; Michael L. Littman; Alexander J. Smola (CoRR, 2021)

Faster Deep Reinforcement Learning with Slower Online Network. - Kavosh Asadi; Rasool Fakoor; Omer Gottesman; Taesup Kim; Michael L. Littman; Alexander J. Smola (NeurIPS, 2022)

Adaptive Interest for Emphatic Reinforcement Learning. - Martin Klissarov; Rasool Fakoor; Jonas W. Mueller; Kavosh Asadi; Taesup Kim; Alexander J. Smola (NeurIPS, 2022)

Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline. - Massimo Caccia; Jonas Mueller 001; Taesup Kim; Laurent Charlin; Rasool Fakoor (CoRR, 2022)

Data drift correction via time-varying importance weight estimator. - Rasool Fakoor; Jonas Mueller 001; Zachary C. Lipton; Pratik Chaudhari; Alexander J. Smola (CoRR, 2022)

Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. - Massimo Caccia; Jonas Mueller 001; Taesup Kim; Laurent Charlin; Rasool Fakoor (CoLLAs, 2023)

Budgeting Counterfactual for Offline RL. - Yao Liu 009; Pratik Chaudhari; Rasool Fakoor (NeurIPS, 2023)

Resetting the Optimizer in Deep RL: An Empirical Study. - Kavosh Asadi; Rasool Fakoor; Shoham Sabach (NeurIPS, 2023)

TD Convergence: An Optimization Perspective. - Kavosh Asadi; Shoham Sabach; Yao Liu 009; Omer Gottesman; Rasool Fakoor (NeurIPS, 2023)

Flexible Model Aggregation for Quantile Regression. - Rasool Fakoor; Taesup Kim; Jonas Mueller 001; Alexander J. Smola; Ryan J. Tibshirani (J. Mach. Learn. Res., 2023)

EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRL, 2024)

Time-Varying Propensity Score to Bridge the Gap between the Past and Present. - Rasool Fakoor; Jonas Mueller 001; Zachary Chase Lipton; Pratik Chaudhari; Alex Smola (ICLR, 2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. - Zuxin Liu; Jesse Zhang; Kavosh Asadi; Yao Liu 009; Ding Zhao; Shoham Sabach; Rasool Fakoor (ICLR, 2024)

Learning the Target Network in Function Space. - Kavosh Asadi; Yao Liu 009; Shoham Sabach; Ming Yin; Rasool Fakoor (ICML, 2024)

AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Search. - Wei Tang; Yiheng Duan; Yaroslav Kharkov; Rasool Fakoor; Eric Kessler; Yunong Shi (QCE, 2024)

EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRR, 2024)

AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. - Ke Yang 003; Yao Liu 009; Sapana Chaudhary; Rasool Fakoor; Pratik Chaudhari; George Karypis; Huzefa Rangwala (ICLR, 2025)

Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. - Zhepeng Cen; Yao Liu 009; Siliang Zeng; Pratik Chaudhari; Huzefa Rangwala; George Karypis; Rasool Fakoor (Trans. Mach. Learn. Res., 2025)

From Demonstrations to Rewards: Alignment Without Explicit Human Preferences. - Siliang Zeng; Yao Liu 009; Huzefa Rangwala; George Karypis; Mingyi Hong 001; Rasool Fakoor (CoRR, 2025)

Teaching Large Language Models to Reason through Learning and Forgetting. - Tianwei Ni; Allen Nie; Sapana Chaudhary; Yao Liu 009; Huzefa Rangwala; Rasool Fakoor (CoRR, 2025)