Paulo Orenstein

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 12

Top Topics

Uniform Quantization

Bias Correction

Top Venues

J. Mach. Learn. Res.

Publications

Thiago Ramos, Rodrigo Loro Schuller, Alex Akira Okuno, Lucas Nissenbaum, Roberto I Oliveira, Paulo Orenstein
BlockBoost: Scalable and Efficient Blocking through Boosting. AISTATS (2024)
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking. NeurIPS (2023)
Lucas R. Schwengber, Lucas Resende, Paulo Orenstein, Roberto I. Oliveira
Deep Hashing via Householder Quantization. CoRR (2023)
Daniel Csillag, Lucas Monteiro Paes, Thiago Ramos, João Vitor Romano, Rodrigo Schuller, Roberto de Beauclair Seixas, Roberto I. Oliveira, Paulo Orenstein
AmnioML: Amniotic Fluid Segmentation and Volume Prediction with Uncertainty Quantification. AAAI (2023)
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey
Adaptive Bias Correction for Improved Subseasonal Forecasting. CoRR (2022)
Daniel Csillag, Carolina Piazza, Thiago Ramos, João Vitor Romano, Roberto I. Oliveira, Paulo Orenstein
ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics. AISTATS (2022)
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
Learned Benchmarks for Subseasonal Forecasting. CoRR (2021)
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
Online Learning with Optimism and Delay. CoRR (2021)
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
Online Learning with Optimism and Delay. ICML (2021)
James E. Johndrow, Paulo Orenstein, Anirban Bhattacharya
Scalable Approximate MCMC Algorithms for the Horseshoe Prior. J. Mach. Learn. Res. 21 (2020)
Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. KDD (2019)
Jessica Hwang, Paulo Orenstein, Karl Pfeiffer, Judah Cohen, Lester Mackey
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. CoRR (2018)