410 citations · 583 across the 38 of their papers we have counts for
8 papers · 1 filter
Does On-Policy Distillation Need to Complete Every Rollout?
Zhengxin Zhang, Maosen Tang, Ning Wang +6
On-policy distillation (OPD) transfers teacher knowledge to a student through feedback on student-generated rollouts, but generating complete rollouts and computing per-token teach…
HARP: Efficient Data Selection for Finetuning Large Language Models
Ning Wang, Zhengxin Zhang, Maosen Tang +3
Finetuning data selection requires balancing two competing goals: selecting examples that improve the downstream objective, and doing so without repeatedly finetuning models. Train…
Metric -clustering using only Weak Comparison Oracles
Rahul Raychaudhury, Aryan Esmailpour, Sainyam Galhotra +1
Clustering is a fundamental primitive in unsupervised learning. However, classical algorithms for -clustering (such as -median and -means) assume access to exact pairwise…
Benchmarking Robust Aggregation in Decentralized Gradient Marketplaces
Zeyu Song, Sainyam Galhotra, Shagufta Mehnaz
The rise of distributed and privacy-preserving machine learning has sparked interest in decentralized gradient marketplaces, where participants trade intermediate artifacts like gr…
SIFOTL: A Principled, Statistically-Informed Fidelity-Optimization Method for Tabular Learning
Shubham Mohole, Sainyam Galhotra
Identifying the factors driving data shifts in tabular datasets is a significant challenge for analysis and decision support systems, especially those focusing on healthcare. Priva…
Optimal Pricing for Data-Augmented AutoML Marketplaces
Minbiao Han, Jonathan Light, Steven Xia +3
Organizations often lack sufficient data to effectively train machine learning (ML) models, while others possess valuable data that remains underutilized. Data markets promise to u…
Consistent Range Approximation for Fair Predictive Modeling
Jiongli Zhu, Sainyam Galhotra, Nazanin Sabri +1
This paper proposes a novel framework for certifying the fairness of predictive models trained on biased data. It draws from query answering for incomplete and inconsistent databas…
Causal Feature Selection for Algorithmic Fairness
Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri +1
The use of machine learning (ML) in high-stakes societal decisions has encouraged the consideration of fairness throughout the ML lifecycle. Although data integration is one of the…