22 citations · 84 across the 31 of their papers we have counts for
10 papers · 1 filter
Distributed Sparse Multicategory Discriminant Analysis
Hengchao Chen, Qiang Sun
This paper proposes a convex formulation for sparse multicategory linear discriminant analysis and then extend it to the distributed setting when data are stored across multiple si…
A provable two-stage algorithm for penalized hazards regression
Jianqing Fan, Wenyan Gong, Qiang Sun
From an optimizer's perspective, achieving the global optimum for a general nonconvex problem is often provably NP-hard using the classical worst-case analysis. In the case of Cox'…
Bayesian high-dimensional linear regression with generic spike-and-slab priors
Bai Jiang, Qiang Sun
Spike-and-slab priors are popular Bayesian solutions for high-dimensional linear regression problems. Previous theoretical studies on spike-and-slab methods focus on specific prior…
Iteratively Reweighted -Penalized Robust Regression
Xiaoou Pan, Qiang Sun, Wen-Xin Zhou
This paper investigates tradeoffs among optimization errors, statistical rates of convergence and the effect of heavy-tailed errors for high-dimensional robust regression with nonc…
Gaussian Approximations for Maxima of Random Vectors under -th Moments
Qiang Sun
We derive a Gaussian approximation result for the maximum of a sum of random vectors under -th moments. Our main theorem is abstract and nonasymptotic, and can be applied to…
Exact Cluster Recovery via Classical Multidimensional Scaling
Anna Little, Yuying Xie, Qiang Sun
Classical multidimensional scaling is an important dimension reduction technique. Yet few theoretical results characterizing its statistical performance exist. This paper provides…
Bernstein's inequalities for general Markov chains
Bai Jiang, Qiang Sun, Jianqing Fan
We establish Bernstein's inequalities for functions of general (general-state-space and possibly non-reversible) Markov chains. These inequalities achieve sharp variance proxies an…
Hoeffding's lemma for Markov Chains and its applications to statistical learning
Jianqing Fan, Bai Jiang, Qiang Sun
We extend Hoeffding's lemma to general-state-space and not necessarily reversible Markov chains. Let be a stationary Markov chain with invariant measure and…
Adaptive Huber Regression
Qiang Sun, Wenxin Zhou, Jianqing Fan
Big data can easily be contaminated by outliers or contain variables with heavy-tailed distributions, which makes many conventional methods inadequate. To address this challenge, w…
I-LAMM for Sparse Learning: Simultaneous Control of Algorithmic Complexity and Statistical Error
Jianqing Fan, Han Liu, Qiang Sun +1
We propose a computational framework named iterative local adaptive majorize-minimization (I-LAMM) to simultaneously control algorithmic complexity and statistical error when fitti…