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20132023
most citedTheoretically Principled Trade-off between Robustness and Accuracy

921 citations · 1.4k across the 54 of their papers we have counts for

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6 papers · 1 filter

stat.ML2020★ 1 cited

Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers

Fan Yang, Hongyang R. Zhang, Sen Wu +2

The problem of learning one task using samples from another task is central to transfer learning. In this paper, we focus on answering the following question: when does combining t…

stat.ML2017

Regression Phalanxes

Hongyang Zhang, William J. Welch, Ruben H. Zamar

Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work we…

stat.ML2017★ 1 cited

Noise-Tolerant Interactive Learning from Pairwise Comparisons

Yichong Xu, Hongyang Zhang, Aarti Singh +2

We study the problem of interactively learning a binary classifier using noisy labeling and pairwise comparison oracles, where the comparison oracle answers which one in the given…

stat.ML2017★ 8 cited

Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions

Maria-Florina Balcan, Hongyang Zhang

We provide new results for noise-tolerant and sample-efficient learning algorithms under -concave distributions. The new class of -concave distributions is a broad and natura…

stat.ML2014★ 1 cited

Multi-rank Sparse Hierarchical Clustering

Hongyang Zhang, Ruben H. Zamar

There has been a surge in the number of large and flat data sets - data sets containing a large number of features and a relatively small number of observations - due to the growin…

stat.ML2013★ 9 cited

A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank

Hongyang Zhang, Zhouchen Lin, Chao Zhang

Rank minimization has attracted a lot of attention due to its robustness in data recovery. To overcome the computational difficulty, rank is often replaced with nuclear norm. For s…