Search Results for author: Yitan Wang

Found 6 papers, 0 papers with code

Fast Submodular Function Maximization

no code implementations15 May 2023 Lianke Qin, Zhao Song, Yitan Wang

We consider both the online and offline versions of the problem: in each iteration, the data set changes incrementally or is not changed, and a user can issue a query to maximize the function on a given subset of the data.

Document Summarization Image Segmentation +1

A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations

no code implementations20 Mar 2023 Siyu Chen, Yitan Wang, Zhaoran Wang, Zhuoran Yang

We study the offline contextual bandit problem, where we aim to acquire an optimal policy using observational data.

Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability

no code implementations15 Oct 2022 Zhao Song, Yitan Wang, Zheng Yu, Lichen Zhang

In this paper, we propose a novel sketching scheme for the first order method in large-scale distributed learning setting, such that the communication costs between distributed agents are saved while the convergence of the algorithms is still guaranteed.

Federated Learning

A Sublinear Adversarial Training Algorithm

no code implementations10 Aug 2022 Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang

For a neural network of width $m$, $n$ input training data in $d$ dimension, it takes $\Omega(mnd)$ time cost per training iteration for the forward and backward computation.

Succinct Explanations With Cascading Decision Trees

no code implementations13 Oct 2020 Jialu Zhang, Yitan Wang, Mark Santolucito, Ruzica Piskac

The decision tree is one of the most popular and classical machine learning models from the 1980s.

Classification General Classification

Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks

no code implementations17 May 2018 Guangzeng Xie, Yitan Wang, Shuchang Zhou, Zhihua Zhang

In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks.

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