Rishi Saket

Rishi Saket

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Generalization and Learnability in Multiple Instance Regression
Kushal Chauhan
Rishi Saket
Lorne Applebaum
Ashwinkumar Badanidiyuru Varadaraja
Chandan Giri
Aravindan Raghuveer
Proc. UAI (2024)
LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions
Anand Brahmbhatt
Mohith Pokala
Rishi Saket
Aravindan Raghuveer
Proc. CIKM Applied Research Track (2024)
Hardness of Learning Boolean Functions from Label Proportions
Venkatesan Guruswami
Rishi Saket
Proc. FSTTCS (2023)
Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets
Jay Nandy
Jatin Chauhan
Rishi Saket
Aravindan Raghuveer
CIKM (2023)
PAC Learning Linear Thresholds from Label Proportions
Anand Brahmbhatt
Rishi Saket
Aravindan Raghuveer
Proc. NeurIPS (2023)
On Combining Bags to Better Learn from Label Proportions
Rishi Saket
Aravindan Raghuveer
Balaraman Ravindran
Proc. AISTATS'22 (2022)
Multi-Variate Time Series Forecasting on Variable Subsets
Jatin Chauhan
Aravindan Raghuveer
Jay Nandy
Rishi Saket
Balaraman Ravindran
KDD 2022
Algorithms and Hardness for Learning Linear Thresholds from Label Proportions
Rishi Saket
Proc. NeurIPS'22 (2022)
Domain-Agnostic Contrastive Representations for Learning from Label Proportions
Jay Nandy
Rishi Saket
Prateek Jain
Jatin Chauhan
Balaraman Ravindran
Aravindan Raghuveer
Proc. CIKM 2022
Learnability of Linear Thresholds from Label Proportions
Rishi Saket
Proc. NeurIPS'21 (2021)
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