6 citations · 20 across the 25 of their papers we have counts for
9 papers · 1 filter
Self-Indexing KVCache: Predicting Sparse Attention from Compressed Keys
Xu Yang, Jiapeng Zhang, Dongyang Zhao +2
The KV cache in self-attention has emerged as a major bottleneck in long-context and large-batch inference for LLMs. Existing approaches often treat sparsity prediction and compres…
CoreSPECT: Enhancing Clustering Algorithms via an Interplay of Density and Geometry
Chandra Sekhar Mukherjee, Joonyoung Bae, Jiapeng Zhang
In this paper, we provide a novel perspective on the underlying structure of real-world data with ground-truth clusters via characterization of an abundantly observed yet often ove…
A multi-core periphery perspective: Ranking via relative centrality
Chandra Sekhar Mukherjee, Jiapeng Zhang
Community and core-periphery are two widely studied graph structures, with their coexistence observed in real-world graphs (Rombach, Porter, Fowler \& Mucha [SIAM J. App. Math. 201…
On the Power of SVD in the Stochastic Block Model
Xinyu Mao, Jiapeng Zhang
A popular heuristic method for improving clustering results is to apply dimensionality reduction before running clustering algorithms. It has been observed that spectral-based dime…
Confident Clustering via PCA Compression Ratio and Its Application to Single-cell RNA-seq Analysis
Yingcong Li, Chandra Sekhar Mukherjee, Jiapeng Zhang
Unsupervised clustering algorithms for vectors has been widely used in the area of machine learning. Many applications, including the biological data we studied in this paper, cont…
Capturing the Denoising Effect of PCA via Compression Ratio
Chandra Sekhar Mukherjee, Nikhil Doerkar, Jiapeng Zhang
Principal component analysis (PCA) is one of the most fundamental tools in machine learning with broad use as a dimensionality reduction and denoising tool. In the later setting, w…
Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle
Chandra Sekhar Mukherjee, Pan Peng, Jiapeng Zhang
The stochastic block model (SBM) is a fundamental model for studying graph clustering or community detection in networks. It has received great attention in the last decade and the…
Towards a Query-Optimal and Time-Efficient Algorithm for Clustering with a Faulty Oracle
Pan Peng, Jiapeng Zhang
Motivated by applications in crowdsourced entity resolution in database, signed edge prediction in social networks and correlation clustering, Mazumdar and Saha [NIPS 2017] propose…
Active classification with comparison queries
Daniel M. Kane, Shachar Lovett, Shay Moran +1
We study an extension of active learning in which the learning algorithm may ask the annotator to compare the distances of two examples from the boundary of their label-class. For…