Paul Mineiro - RankMe

75 papers A* 20A 1Journal 44Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interaction-Grounded Learning for Contextual Markov Decision Processes with Personalized Feedback. CoRR Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
2024	A*	`conf`	Active, anytime-valid risk controlling prediction sets. NeurIPS Ziyu Xu, Nikos Karampatziakis, Paul Mineiro
2024	J	`jnl`	Active, anytime-valid risk controlling prediction sets. CoRR Ziyu Xu, Nikos Karampatziakis, Paul Mineiro
2024	A*	`conf`	Aligning LLM Agents by Learning Latent Preference from User Edits. NeurIPS Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra
2024	J	`jnl`	Aligning LLM Agents by Learning Latent Preference from User Edits. CoRR Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra
2024	A*	`conf`	Efficient Contextual Bandits with Uninformed Feedback Graphs. ICML Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
2024	J	`jnl`	Efficient Contextual Bandits with Uninformed Feedback Graphs. CoRR Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
2024	J	`jnl`	Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning. CoRR Yihe Deng, Paul Mineiro
2024	J	`jnl`	Online Joint Fine-tuning of Multi-Agent Flows. CoRR Paul Mineiro
2024	A*	`conf`	Provably Efficient Interactive-Grounded Learning with Personalized Reward. NeurIPS Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
2024	J	`jnl`	Provably Efficient Interactive-Grounded Learning with Personalized Reward. CoRR Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
2023	J	`jnl`	Graph Feedback via Reduction to Regression. CoRR Paul Mineiro
2023	A*	`conf`	Infinite Action Contextual Bandits with Reusable Data Exhaust. ICML Mark Rucker, Yinglun Zhu, Paul Mineiro
2023	J	`jnl`	Infinite Action Contextual Bandits with Reusable Data Exhaust. CoRR Mark Rucker, Yinglun Zhu, Paul Mineiro
2023	A*	`conf`	Personalized Reward Learning with Interaction-Grounded Learning (IGL). ICLR Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, Cheng Tan
2023	A*	`conf`	Practical Contextual Bandits with Feedback Graphs. NeurIPS Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro
2023	A*	`conf`	Time-uniform confidence bands for the CDF under nonstationarity. NeurIPS Paul Mineiro, Steven R. Howard
2023	J	`jnl`	Time-uniform confidence bands for the CDF under nonstationarity. CoRR Paul Mineiro, Steven R. Howard
2022	J	`jnl`	A lower confidence sequence for the changing mean of non-negative right heavy-tailed observations with bounded mean. CoRR Paul Mineiro
2022	J	`jnl`	Anytime-valid off-policy inference for contextual bandits. CoRR Ian Waudby-Smith, Lili Wu, Aaditya Ramdas, Nikos Karampatziakis, Paul Mineiro
2022	J	`jnl`	Conditionally Risk-Averse Contextual Bandits. CoRR Mónika Farsang, Paul Mineiro, Wangda Zhang
2022	A*	`conf`	Contextual Bandits with Large Action Spaces: Made Practical. ICML Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro
2022	J	`jnl`	Contextual Bandits with Large Action Spaces: Made Practical. CoRR Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro
2022	A*	`conf`	Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. ICML Yinglun Zhu, Paul Mineiro
2022	J	`jnl`	Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. CoRR Yinglun Zhu, Paul Mineiro
2022	—	`conf`	Deploying a Steered Query Optimizer in Production at Microsoft. SIGMOD Conference Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022	J	`jnl`	Deploying a Steered Query Optimizer in Production at Microsoft. CoRR Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
2022	J	`jnl`	Eigen Memory Trees. CoRR Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro, Ida Momennejad
2022	—	`conf`	Interaction-Grounded Learning for Recommender Systems. ORSUM@RecSys Jessica Maghakian, Kishan Panaganti, Paul Mineiro, Akanksha Saran, Cheng Tan
2022	A*	`conf`	Interaction-Grounded Learning with Action-Inclusive Feedback. NeurIPS Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
2022	J	`jnl`	Interaction-Grounded Learning with Action-inclusive Feedback. CoRR Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
2022	J	`jnl`	Personalized Reward Learning with Interaction-Grounded Learning (IGL). CoRR Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, Cheng Tan
2022	J	`jnl`	Towards Data-Driven Offline Simulations for Online Reinforcement Learning. CoRR Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
2021	A*	`conf`	Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	J	`jnl`	Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
2021	A*	`conf`	ChaCha for Online AutoML. ICML Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021	J	`jnl`	ChaCha for Online AutoML. CoRR Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021	J	`jnl`	Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL. CoRR Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan
2021	A*	`conf`	Interaction-Grounded Learning. ICML Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021	J	`jnl`	Interaction-Grounded Learning. CoRR Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021	A*	`conf`	Off-Policy Confidence Sequences. ICML Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021	J	`jnl`	Off-policy Confidence Sequences. CoRR Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2020	A*	`conf`	Empirical Likelihood for Contextual Bandits. NeurIPS Nikos Karampatziakis, John Langford, Paul Mineiro
2019	A*	`conf`	Contextual Memory Trees. ICML Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2019	J	`jnl`	Empirical Likelihood for Contextual Bandits. CoRR Nikos Karampatziakis, John Langford, Paul Mineiro
2019	J	`jnl`	Lessons from Real-World Reinforcement Learning in a Customer Support Bot. CoRR Nikos Karampatziakis, Sebastian Kochman, Jade Huang, Paul Mineiro, Kathy Osborne, Weizhu Chen
2018	J	`jnl`	Contextual Memory Trees. CoRR Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2017	A*	`conf`	Logarithmic Time One-Against-Some. ICML Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
2016	J	`jnl`	Active Information Acquisition. CoRR He He, Paul Mineiro, Nikos Karampatziakis
2016	J	`jnl`	Learning Reductions That Really Work. Proc. IEEE Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2016	J	`jnl`	Logarithmic Time One-Against-Some. CoRR Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
2015	J	`jnl`	A Hierarchical Spectral Method for Extreme Classification. CoRR Paul Mineiro, Nikos Karampatziakis
2015	—	`conf`	Fast Label Embeddings for Extremely Large Output Spaces. ICLR (Workshop) Paul Mineiro, Nikos Karampatziakis
2015	—	`conf`	Fast Label Embeddings via Randomized Linear Algebra. ECML/PKDD (1) Paul Mineiro, Nikos Karampatziakis
2015	J	`jnl`	Learning Reductions that Really Work. CoRR Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
2015	J	`jnl`	Multilabel Prediction via Calibration. CoRR Nikos Karampatziakis, Paul Mineiro
2014	J	`jnl`	A Randomized Algorithm for CCA. CoRR Paul Mineiro, Nikos Karampatziakis
2014	A*	`conf`	Discriminative Features via Generalized Eigenvectors. ICML Nikos Karampatziakis, Paul Mineiro
2014	J	`jnl`	Fast Label Embeddings for Extremely Large Output Spaces. CoRR Paul Mineiro, Nikos Karampatziakis
2014	J	`jnl`	Normalized Online Learning. CoRR Stéphane Ross, Paul Mineiro, John Langford
2013	J	`jnl`	Combining Structured and Unstructured Randomness in Large Scale PCA. CoRR Nikos Karampatziakis, Paul Mineiro
2013	J	`jnl`	Discriminative Features via Generalized Eigenvectors. CoRR Nikos Karampatziakis, Paul Mineiro
2013	—	`conf`	Loss-Proportional Subsampling for Subsequent ERM. ICML (3) Paul Mineiro, Nikos Karampatziakis
2013	J	`jnl`	Loss-Proportional Subsampling for Subsequent ERM. CoRR Paul Mineiro, Nikos Karampatziakis
2013	—	`conf`	Machine learning for big data. SIGMOD Conference Tyson Condie, Paul Mineiro, Neoklis Polyzotis, Markus Weimer
2013	A*	`conf`	Machine learning on Big Data. ICDE Tyson Condie, Paul Mineiro, Neoklis Polyzotis, Markus Weimer
2013	J	`jnl`	Normalized Online Learning CoRR Stéphane Ross, Paul Mineiro, John Langford
2013	A	`conf`	Normalized Online Learning. UAI Stéphane Ross, Paul Mineiro, John Langford
2002	J	`jnl`	A Monte Carlo EM Approach for Partially Observable Diffusion Processes: Theory and Applications to Neural Networks. Neural Comput. Javier R. Movellan, Paul Mineiro, Ruth J. Williams
2000	—	`conf`	Partially Observable SDE Models for Image Sequence Recognition Tasks. NIPS Javier R. Movellan, Paul Mineiro, Ruth J. Williams
1999	—	`conf`	A diffusion network approach to visual speech recognition. AVSP Javier R. Movellan, Paul Mineiro
1998	J	`jnl`	Analysis of Direction Selectivity Arising From Recurrent Cortical Interactions. Neural Comput. Paul Mineiro, David Zipser
1998	J	`jnl`	Robust Sensor Fusion: Analysis and Application to Audio Visual Speech Recognition. Mach. Learn. Javier R. Movellan, Paul Mineiro
1997	—	`conf`	Bayesian Robustification for Audio Visual Fusion. NIPS Javier R. Movellan, Paul Mineiro
1997	—	`conf`	Learning Path Distributions Using Nonequilibrium Diffusion Networks. NIPS Paul Mineiro, Javier R. Movellan, Ruth J. Williams