3 citations · 7 across the 7 of their papers we have counts for
7 papers
Clustered Linear Contextual Bandits with Knapsacks
Yichuan Deng, Michalis Mamakos, Zhao Song
In this work, we study clustered contextual bandits where rewards and resource consumption are the outcomes of cluster-specific linear models. The arms are divided in clusters, wit…
Convergence of Two-Layer Regression with Nonlinear Units
Yichuan Deng, Zhao Song, Shenghao Xie
Large language models (LLMs), such as ChatGPT and GPT4, have shown outstanding performance in many human life task. Attention computation plays an important role in training LLMs.…
Zero-th Order Algorithm for Softmax Attention Optimization
Yichuan Deng, Zhihang Li, Sridhar Mahadevan +1
Large language models (LLMs) have brought about significant transformations in human society. Among the crucial computations in LLMs, the softmax unit holds great importance. Its h…
Efficient Algorithm for Solving Hyperbolic Programs
Yichuan Deng, Zhao Song, Lichen Zhang +1
Hyperbolic polynomials is a class of real-roots polynomials that has wide range of applications in theoretical computer science. Each hyperbolic polynomial also induces a hyperboli…
Faster Robust Tensor Power Method for Arbitrary Order
Yichuan Deng, Zhao Song, Junze Yin
Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. \emph{Tensor power method} (TPM) is one of the widely-used techniques in the…
Streaming Kernel PCA Algorithm With Small Space
Yichuan Deng, Zhao Song, Zifan Wang +1
Principal Component Analysis (PCA) is a widely used technique in machine learning, data analysis and signal processing. With the increase in the size and complexity of datasets, it…
A Nearly Optimal Size Coreset Algorithm with Nearly Linear Time
Yichuan Deng, Zhao Song, Yitan Wang +1
A coreset is a point set containing information about geometric properties of a larger point set. A series of previous works show that in many machine learning problems, especially…