Search Results for author: Lingxiao Huang

Found 16 papers, 10 papers with code

MuraNet: Multi-task Floor Plan Recognition with Relation Attention

no code implementations1 Sep 2023 Lingxiao Huang, Jung-Hsuan Wu, Chiching Wei, Wilson Li

The recognition of information in floor plan data requires the use of detection and segmentation models.


A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem

no code implementations9 Aug 2023 Zhang-Hua Fu, Sipeng Sun, Jintong Ren, Tianshu Yu, Haoyu Zhang, Yuanyuan Liu, Lingxiao Huang, Xiang Yan, Pinyan Lu

Fair comparisons based on nineteen famous large-scale instances (with 10, 000 to 10, 000, 000 cities) show that HDR is highly competitive against existing state-of-the-art TSP algorithms, in terms of both efficiency and solution quality.

Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions

1 code implementation16 Jun 2023 Niclas Boehmer, L. Elisa Celis, Lingxiao Huang, Anay Mehrotra, Nisheeth K. Vishnoi

We consider the problem of subset selection where one is given multiple rankings of items and the goal is to select the highest ``quality'' subset.


Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering

1 code implementation26 Oct 2022 Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao

Vertical federated learning (VFL), where data features are stored in multiple parties distributively, is an important area in machine learning.

Clustering Federated Learning +1

Coresets for Time Series Clustering

no code implementations NeurIPS 2021 Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi

In particular, we consider the setting where the time series data on $N$ entities is generated from a Gaussian mixture model with autocorrelations over $k$ clusters in $\mathbb{R}^d$.

Clustering Time Series +1

Clustering Aware Classification for Risk Prediction and Subtyping in Clinical Data

1 code implementation23 Feb 2021 Shivin Srivastava, Siddharth Bhatia, Lingxiao Huang, Lim Jun Heng, Kenji Kawaguchi, Vaibhav Rajan

In data containing heterogeneous subpopulations, classification performance benefits from incorporating the knowledge of cluster structure in the classifier.

Classification Clustering +2

Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching

2 code implementations16 Dec 2020 Chang Liu, Zetian Jiang, Runzhong Wang, Junchi Yan, Lingxiao Huang, Pinyan Lu

As such, the agent can finish inlier matching timely when the affinity score stops growing, for which otherwise an additional parameter i. e. the number of inliers is needed to avoid matching outliers.

Combinatorial Optimization Decision Making +3

Coresets for Regressions with Panel Data

1 code implementation NeurIPS 2020 Lingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi

We first define coresets for several variants of regression problems with panel data and then present efficient algorithms to construct coresets of size that depend polynomially on 1/$\varepsilon$ (where $\varepsilon$ is the error parameter) and the number of regression parameters - independent of the number of individuals in the panel data or the time units each individual is observed for.


Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees

1 code implementation8 Jun 2020 L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi

We present an optimization framework for learning a fair classifier in the presence of noisy perturbations in the protected attributes.

Fairness General Classification

Coresets for Clustering with Fairness Constraints

1 code implementation NeurIPS 2019 Lingxiao Huang, Shaofeng H. -C. Jiang, Nisheeth K. Vishnoi

Our approach is based on novel constructions of coresets: for the $k$-median objective, we construct an $\varepsilon$-coreset of size $O(\Gamma k^2 \varepsilon^{-d})$ where $\Gamma$ is the number of distinct collections of groups that a point may belong to, and for the $k$-means objective, we show how to construct an $\varepsilon$-coreset of size $O(\Gamma k^3\varepsilon^{-d-1})$.

Clustering Fairness

Stable and Fair Classification

1 code implementation21 Feb 2019 Lingxiao Huang, Nisheeth K. Vishnoi

Theoretically, we prove a stability guarantee, that was lacking in fair classification algorithms, and also provide an accuracy guarantee for our extended framework.

Classification Decision Making +2

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

4 code implementations15 Jun 2018 L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi

The main contribution of this paper is a new meta-algorithm for classification that takes as input a large class of fairness constraints, with respect to multiple non-disjoint sensitive attributes, and which comes with provable guarantees.

Classification Fairness +1

Multiwinner Voting with Fairness Constraints

1 code implementation27 Oct 2017 L. Elisa Celis, Lingxiao Huang, Nisheeth K. Vishnoi

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters.


SVM via Saddle Point Optimization: New Bounds and Distributed Algorithms

no code implementations20 May 2017 Yifei Jin, Lingxiao Huang, Jian Li

Our algorithms achieve $(1-\epsilon)$-approximations with running time $\tilde{O}(nd+n\sqrt{d / \epsilon})$ for both variants, where $n$ is the number of points and $d$ is the dimensionality.

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