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2020 – today
- 2024
[j2]Roberto I. Oliveira, Paulo Orenstein, Thiago Ramos, João Vitor Romano:
Split Conformal Prediction and Non-Exchangeable Data. J. Mach. Learn. Res. 25: 225:1-225:38 (2024)- [c6]Thiago Ramos, Rodrigo Loro Schuller, Alex Akira Okuno, Lucas Nissenbaum, Roberto I Oliveira, Paulo Orenstein:
BlockBoost: Scalable and Efficient Blocking through Boosting. AISTATS 2024: 2575-2583 - 2023
- [c5]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: 15494-15502 - [c4]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 - [i5]Lucas R. Schwengber, Lucas Resende, Paulo Orenstein, Roberto I. Oliveira:
Deep Hashing via Householder Quantization. CoRR abs/2311.04207 (2023) - 2022
- [c3]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: 9017-9049 - [i4]Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey:
Adaptive Bias Correction for Improved Subseasonal Forecasting. CoRR abs/2209.10666 (2022) - 2021
- [c2]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. ICML 2021: 3363-3373 - [i3]Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey:
Online Learning with Optimism and Delay. CoRR abs/2106.06885 (2021) - [i2]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 abs/2109.10399 (2021) - 2020
- [j1]James E. Johndrow, Paulo Orenstein, Anirban Bhattacharya:
Scalable Approximate MCMC Algorithms for the Horseshoe Prior. J. Mach. Learn. Res. 21: 73:1-73:61 (2020)
2010 – 2019
- 2019
- [c1]Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey:
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. KDD 2019: 2325-2335 - 2018
- [i1]Jessica Hwang, Paulo Orenstein, Karl Pfeiffer, Judah Cohen, Lester Mackey:
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. CoRR abs/1809.07394 (2018)
Coauthor Index
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