Search Results for author: Jason Xu

Found 15 papers, 5 papers with code

The Stochastic Proximal Distance Algorithm

no code implementations21 Oct 2022 Haoyu Jiang, Jason Xu

Stochastic versions of proximal methods have gained much attention in statistics and machine learning.

Bregman Power k-Means for Clustering Exponential Family Data

1 code implementation22 Jun 2022 Adithya Vellal, Saptarshi Chakraborty, Jason Xu

Recent progress in center-based clustering algorithms combats poor local minima by implicit annealing, using a family of generalized means.

Wi-Fi and Bluetooth Contact Tracing Without User Intervention

no code implementations31 Mar 2022 Brosnan Yuen, Yifeng Bie, Duncan Cairns, Geoffrey Harper, Jason Xu, Charles Chang, Xiaodai Dong, Tao Lu

Previous contact tracing systems required the users to perform many manual actions, such as installing smartphone applications, joining wireless networks, or carrying custom user devices.

Privacy Preserving

Computational tools for assessing gene therapy under branching process models of mutation

no code implementations16 Nov 2021 Timothy C Stutz, Janet S. Sinsheimer, Mary Sehl, Jason Xu

In our model, a single-hit mutation carries a slight proliferative advantage over a wild-type stem cells.

Uniform Concentration Bounds toward a Unified Framework for Robust Clustering

1 code implementation NeurIPS 2021 Debolina Paul, Saptarshi Chakraborty, Swagatam Das, Jason Xu

Recent advances in center-based clustering continue to improve upon the drawbacks of Lloyd's celebrated $k$-means algorithm over $60$ years after its introduction.

Community Detection in Weighted Multilayer Networks with Ambient Noise

1 code implementation24 Feb 2021 Mark He, Dylan Lu, Jason Xu, Rose Mary Xavier

We call this model for multilayer weighted networks the Stochastic Block (with) Ambient Noise Model (SBANM) and develop an associated community detection algorithm.

Community Detection Variational Inference

Kernel k-Means, By All Means: Algorithms and Strong Consistency

no code implementations12 Nov 2020 Debolina Paul, Saptarshi Chakraborty, Swagatam Das, Jason Xu

We show the method implicitly performs annealing in kernel feature space while retaining efficient, closed-form updates, and we rigorously characterize its convergence properties both from computational and statistical points of view.

Simple and Scalable Sparse k-means Clustering via Feature Ranking

1 code implementation NeurIPS 2020 Zhiyue Zhang, Kenneth Lange, Jason Xu

In this paper, we propose a novel framework for sparse k-means clustering that is intuitive, simple to implement, and competitive with state-of-the-art algorithms.

Entropy Regularized Power k-Means Clustering

1 code implementation10 Jan 2020 Saptarshi Chakraborty, Debolina Paul, Swagatam Das, Jason Xu

Despite its well-known shortcomings, $k$-means remains one of the most widely used approaches to data clustering.

Structural Risk Minimization for $C^{1,1}(\mathbb{R}^d)$ Regression

no code implementations29 Mar 2018 Adam Gustafson, Matthew Hirn, Kitty Mohammed, Hariharan Narayanan, Jason Xu

Recently, the following smooth function approximation problem was proposed: given a finite set $E \subset \mathbb{R}^d$ and a function $f: E \rightarrow \mathbb{R}$, interpolate the given information with a function $\widehat{f} \in \dot{C}^{1, 1}(\mathbb{R}^d)$ (the class of first-order differentiable functions with Lipschitz gradients) such that $\widehat{f}(a) = f(a)$ for all $a \in E$, and the value of $\mathrm{Lip}(\nabla \widehat{f})$ is minimal.


Automatic Conflict Detection in Police Body-Worn Audio

no code implementations14 Nov 2017 Alistair Letcher, Jelena Trišović, Collin Cademartori, Xi Chen, Jason Xu

Automatic conflict detection has grown in relevance with the advent of body-worn technology, but existing metrics such as turn-taking and overlap are poor indicators of conflict in police-public interactions.

An MM Algorithm for Split Feasibility Problems

no code implementations16 Dec 2016 Jason Xu, Eric C. Chi, Meng Yang, Kenneth Lange

Furthermore, we show that the Euclidean norm appearing in the proximity function of the non-linear split feasibility problem can be replaced by arbitrary Bregman divergences.

Stochastic Variational Inference for Hidden Markov Models

no code implementations NeurIPS 2014 Nicholas J. Foti, Jason Xu, Dillon Laird, Emily B. Fox

Variational inference algorithms have proven successful for Bayesian analysis in large data settings, with recent advances using stochastic variational inference (SVI).

Stochastic Optimization Variational Inference

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