Paul Mineiro

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 50

Top Topics

Information Acquisition

Query Optimizer

Reinforcement Learning

Top Venues

Publications

Ziyu Xu, Nikos Karampatziakis, Paul Mineiro
Active, anytime-valid risk controlling prediction sets. CoRR (2024)
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
Provably Efficient Interactive-Grounded Learning with Personalized Reward. CoRR (2024)
Paul Mineiro
Online Joint Fine-tuning of Multi-Agent Flows. CoRR (2024)
Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro
Efficient Contextual Bandits with Uninformed Feedback Graphs. CoRR (2024)
Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra
Aligning LLM Agents by Learning Latent Preference from User Edits. CoRR (2024)
Paul Mineiro, Steven R. Howard
Time-uniform confidence bands for the CDF under nonstationarity. NeurIPS (2023)
Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, Cheng Tan
Personalized Reward Learning with Interaction-Grounded Learning (IGL). ICLR (2023)
Paul Mineiro
Graph Feedback via Reduction to Regression. CoRR (2023)
Mark Rucker, Yinglun Zhu, Paul Mineiro
Infinite Action Contextual Bandits with Reusable Data Exhaust. CoRR (2023)
Mark Rucker, Yinglun Zhu, Paul Mineiro
Infinite Action Contextual Bandits with Reusable Data Exhaust. ICML (2023)
Paul Mineiro, Steven R. Howard
Time-uniform confidence bands for the CDF under nonstationarity. CoRR (2023)
Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou, Haipeng Luo, Paul Mineiro
Practical Contextual Bandits with Feedback Graphs. NeurIPS (2023)
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
Deploying a Steered Query Optimizer in Production at Microsoft. CoRR (2022)
Jessica Maghakian, Kishan Panaganti, Paul Mineiro, Akanksha Saran, Cheng Tan
Interaction-Grounded Learning for Recommender Systems. ORSUM@RecSys (2022)
Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, Cheng Tan
Personalized Reward Learning with Interaction-Grounded Learning (IGL). CoRR (2022)
Paul Mineiro
A lower confidence sequence for the changing mean of non-negative right heavy-tailed observations with bounded mean. CoRR (2022)
Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
Interaction-Grounded Learning with Action-Inclusive Feedback. NeurIPS (2022)
Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro
Contextual Bandits with Large Action Spaces: Made Practical. CoRR (2022)
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
Towards Data-Driven Offline Simulations for Online Reinforcement Learning. CoRR (2022)
Ian Waudby-Smith, Lili Wu, Aaditya Ramdas, Nikos Karampatziakis, Paul Mineiro
Anytime-valid off-policy inference for contextual bandits. CoRR (2022)
Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal
Deploying a Steered Query Optimizer in Production at Microsoft. SIGMOD Conference (2022)
Yinglun Zhu, Paul Mineiro
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. ICML (2022)
Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford
Interaction-Grounded Learning with Action-inclusive Feedback. CoRR (2022)
Mark Rucker, Jordan T. Ash, John Langford, Paul Mineiro, Ida Momennejad
Eigen Memory Trees. CoRR (2022)
Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro
Contextual Bandits with Large Action Spaces: Made Practical. ICML (2022)
Yinglun Zhu, Paul Mineiro
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. CoRR (2022)
Mónika Farsang, Paul Mineiro, Wangda Zhang
Conditionally Risk-Averse Contextual Bandits. CoRR (2022)
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Interaction-Grounded Learning. CoRR (2021)
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
Off-Policy Confidence Sequences. ICML (2021)
Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL. CoRR (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. CoRR (2021)
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
Off-policy Confidence Sequences. CoRR (2021)
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
ChaCha for Online AutoML. ICML (2021)
Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal
Bellman-consistent Pessimism for Offline Reinforcement Learning. NeurIPS (2021)
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
Interaction-Grounded Learning. ICML (2021)
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
ChaCha for Online AutoML. CoRR (2021)
Nikos Karampatziakis, John Langford, Paul Mineiro
Empirical Likelihood for Contextual Bandits. NeurIPS (2020)
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Contextual Memory Trees. ICML (2019)
Nikos Karampatziakis, John Langford, Paul Mineiro
Empirical Likelihood for Contextual Bandits. CoRR (2019)
Nikos Karampatziakis, Sebastian Kochman, Jade Huang, Paul Mineiro, Kathy Osborne, Weizhu Chen
Lessons from Real-World Reinforcement Learning in a Customer Support Bot. CoRR (2019)
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Contextual Memory Trees. CoRR (2018)
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
Logarithmic Time One-Against-Some. ICML (2017)
He He, Paul Mineiro, Nikos Karampatziakis
Active Information Acquisition. CoRR (2016)
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Learning Reductions That Really Work. Proc. IEEE 104 (1) (2016)
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
Logarithmic Time One-Against-Some. CoRR (2016)
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
Learning Reductions that Really Work. CoRR (2015)
Paul Mineiro, Nikos Karampatziakis
Fast Label Embeddings for Extremely Large Output Spaces. ICLR (Workshop) (2015)
Paul Mineiro, Nikos Karampatziakis
A Hierarchical Spectral Method for Extreme Classification. CoRR (2015)
Nikos Karampatziakis, Paul Mineiro
Multilabel Prediction via Calibration. CoRR (2015)
Paul Mineiro, Nikos Karampatziakis
Fast Label Embeddings via Randomized Linear Algebra. ECML/PKDD (1) (2015)
Paul Mineiro, Nikos Karampatziakis
Fast Label Embeddings for Extremely Large Output Spaces. CoRR (2014)
Paul Mineiro, Nikos Karampatziakis
A Randomized Algorithm for CCA. CoRR (2014)
Nikos Karampatziakis, Paul Mineiro
Discriminative Features via Generalized Eigenvectors. ICML (2014)
Stéphane Ross, Paul Mineiro, John Langford
Normalized Online Learning. CoRR (2014)
Stéphane Ross, Paul Mineiro, John Langford
Normalized Online Learning CoRR (2013)
Tyson Condie, Paul Mineiro, Neoklis Polyzotis, Markus Weimer
Machine learning on Big Data. ICDE (2013)
Stéphane Ross, Paul Mineiro, John Langford
Normalized Online Learning. UAI (2013)
Nikos Karampatziakis, Paul Mineiro
Combining Structured and Unstructured Randomness in Large Scale PCA. CoRR (2013)
Nikos Karampatziakis, Paul Mineiro
Discriminative Features via Generalized Eigenvectors. CoRR (2013)
Tyson Condie, Paul Mineiro, Neoklis Polyzotis, Markus Weimer
Machine learning for big data. SIGMOD Conference (2013)
Paul Mineiro, Nikos Karampatziakis
Loss-Proportional Subsampling for Subsequent ERM. ICML (3) (2013)
Paul Mineiro, Nikos Karampatziakis
Loss-Proportional Subsampling for Subsequent ERM. CoRR (2013)
Javier R. Movellan, Paul Mineiro, Ruth J. Williams
A Monte Carlo EM Approach for Partially Observable Diffusion Processes: Theory and Applications to Neural Networks. Neural Comput. 14 (7) (2002)
Javier R. Movellan, Paul Mineiro, Ruth J. Williams
Partially Observable SDE Models for Image Sequence Recognition Tasks. NIPS (2000)
Javier R. Movellan, Paul Mineiro
A diffusion network approach to visual speech recognition. AVSP (1999)
Javier R. Movellan, Paul Mineiro
Robust Sensor Fusion: Analysis and Application to Audio Visual Speech Recognition. Mach. Learn. 32 (2) (1998)
Paul Mineiro, David Zipser
Analysis of Direction Selectivity Arising From Recurrent Cortical Interactions. Neural Comput. 10 (2) (1998)
Javier R. Movellan, Paul Mineiro
Bayesian Robustification for Audio Visual Fusion. NIPS (1997)
Paul Mineiro, Javier R. Movellan, Ruth J. Williams
Learning Path Distributions Using Nonequilibrium Diffusion Networks. NIPS (1997)