Search Results for author: Olgica Milenkovic

Found 26 papers, 7 papers with code

Highly Scalable and Provably Accurate Classification in Poincare Balls

1 code implementation8 Sep 2021 Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic

For hierarchical data, the space of choice is a hyperbolic space since it guarantees low-distortion embeddings for tree-like structures.

Classification Time Series

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

no code implementations24 Jun 2021 Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic

We propose AllSet, a new hypergraph neural network paradigm that represents a highly general framework for (hyper)graph neural networks and for the first time implements hypergraph neural network layers as compositions of two multiset functions that can be efficiently learned for each task and each dataset.

Node Classification

Query-Based Selection of Optimal Candidates under the Mallows Model

no code implementations18 Jan 2021 Xujun Liu, Olgica Milenkovic, George V. Moustakides

If the Genie confirms the query, the selection process terminates.

Methodology Discrete Mathematics Information Theory Combinatorics Information Theory 05A

AC-DC: Amplification Curve Diagnostics for Covid-19 Group Testing

no code implementations10 Nov 2020 Ryan Gabrys, Srilakshmi Pattabiraman, Vishal Rana, João Ribeiro, Mahdi Cheraghchi, Venkatesan Guruswami, Olgica Milenkovic

The first part of the paper presents a review of the gold-standard testing protocol for Covid-19, real-time, reverse transcriptase PCR, and its properties and associated measurement data such as amplification curves that can guide the development of appropriate and accurate adaptive group testing protocols.

Geometry of Similarity Comparisons

no code implementations17 Jun 2020 Puoya Tabaghi, Jianhao Peng, Olgica Milenkovic, Ivan Dokmanić

To study this question, we introduce the notions of the \textit{ordinal capacity} of a target space form and \emph{ordinal spread} of the similarity measurements.

Adaptive Universal Generalized PageRank Graph Neural Network

1 code implementation ICLR 2021 Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic

We address these issues by introducing a new Generalized PageRank (GPR) GNN architecture that adaptively learns the GPR weights so as to jointly optimize node feature and topological information extraction, regardless of the extent to which the node labels are homophilic or heterophilic.

GPR Node Classification +1

Support Estimation with Sampling Artifacts and Errors

no code implementations14 Jun 2020 Eli Chien, Olgica Milenkovic, Angelia Nedich

Here we introduce the first known approach to support estimation in the presence of sampling artifacts and errors where each sample is assumed to arise from a Poisson repeat channel which simultaneously captures repetitions and deletions of samples.

Multi-MotifGAN (MMGAN): Motif-targeted Graph Generation and Prediction

no code implementations8 Nov 2019 Anuththari Gamage, Eli Chien, Jianhao Peng, Olgica Milenkovic

Generative models are successful at retaining pairwise associations in the underlying networks but often fail to capture higher-order connectivity patterns known as network motifs.

Graph Generation

Image processing in DNA

no code implementations22 Oct 2019 Chao Pan, S. M. Hossein Tabatabaei Yazdi, S Kasra Tabatabaei, Alvaro G. Hernandez, Charles Schroeder, Olgica Milenkovic

The main obstacles for the practical deployment of DNA-based data storage platforms are the prohibitively high cost of synthetic DNA and the large number of errors introduced during synthesis.

Image Inpainting Quantization

Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs

no code implementations20 Oct 2019 Eli Chien, Pan Li, Olgica Milenkovic

We describe the first known mean-field study of landing probabilities for random walks on hypergraphs.

Online Convex Matrix Factorization with Representative Regions

1 code implementation NeurIPS 2019 Abhishek Agarwal, Jianhao Peng, Olgica Milenkovic

We address both problems by proposing the first online convex MF algorithm that maintains a collection of constant-size sets of representative data samples needed for interpreting each of the basis (Ding et al. [2010]) and has the same almost sure convergence guarantees as the online learning algorithm of Mairal et al. [2010].

Dictionary Learning Dimensionality Reduction

Quadratic Decomposable Submodular Function Minimization: Theory and Practice (Computation and Analysis of PageRank over Hypergraphs)

no code implementations26 Feb 2019 Pan Li, Niao He, Olgica Milenkovic

We introduce a new convex optimization problem, termed quadratic decomposable submodular function minimization (QDSFM), which allows to model a number of learning tasks on graphs and hypergraphs.

hypergraph partitioning

Regularized Weighted Chebyshev Approximations for Support Estimation

no code implementations22 Jan 2019 i, Chien, Olgica Milenkovic

We introduce a new method for estimating the support size of an unknown distribution which provably matches the performance bounds of the state-of-the-art techniques in the area and outperforms them in practice.

Higher-Order Spectral Clustering under Superimposed Stochastic Block Model

no code implementations16 Dec 2018 Subhadeep Paul, Olgica Milenkovic, Yuguo Chen

In particular, we prove non-asymptotic upper bounds on the misclustering error of spectral community detection for a SupSBM setting in which triangles or 3-uniform hyperedges are superimposed with undirected edges.

Community Detection Stochastic Block Model

Motif and Hypergraph Correlation Clustering

no code implementations5 Nov 2018 Pan Li, Gregory J. Puleo, Olgica Milenkovic

Our contributions are as follows: We first introduce several variants of motif correlation clustering and then show that these clustering problems are NP-hard.

Quadratic Decomposable Submodular Function Minimization

1 code implementation NeurIPS 2018 Pan Li, Niao He, Olgica Milenkovic

The problem is closely related to decomposable submodular function minimization and arises in many learning on graphs and hypergraphs settings, such as graph-based semi-supervised learning and PageRank.

Query K-means Clustering and the Double Dixie Cup Problem

no code implementations NeurIPS 2018 I Chien, Chao Pan, Olgica Milenkovic

We consider the problem of approximate $K$-means clustering with outliers and side information provided by same-cluster queries and possibly noisy answers.

Revisiting Decomposable Submodular Function Minimization with Incidence Relations

1 code implementation NeurIPS 2018 Pan Li, Olgica Milenkovic

We introduce a new approach to decomposable submodular function minimization (DSFM) that exploits incidence relations.

Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering

1 code implementation ICML 2018 Pan Li, Olgica Milenkovic

We introduce submodular hypergraphs, a family of hypergraphs that have different submodular weights associated with different cuts of hyperedges.

Inhomogeneous Hypergraph Clustering with Applications

1 code implementation NeurIPS 2017 Pan Li, Olgica Milenkovic

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics.

hypergraph partitioning

Efficient Rank Aggregation via Lehmer Codes

no code implementations28 Jan 2017 Pan Li, Arya Mazumdar, Olgica Milenkovic

We propose a novel rank aggregation method based on converting permutations into their corresponding Lehmer codes or other subdiagonal images.

Multiclass MinMax Rank Aggregation

no code implementations28 Jan 2017 Pan Li, Olgica Milenkovic

We introduce a new family of minmax rank aggregation problems under two distance measures, the Kendall {\tau} and the Spearman footrule.

A new correlation clustering method for cancer mutation analysis

no code implementations25 Jan 2016 Jack P. Hou, Amin Emad, Gregory J. Puleo, Jian Ma, Olgica Milenkovic

To test $C^3$, we performed a detailed analysis on TCGA breast cancer and glioblastoma data and showed that our algorithm outperforms the state-of-the-art CoMEt method in terms of discovering mutually exclusive gene modules and identifying driver genes.

Community Detection

Correlation Clustering and Biclustering with Locally Bounded Errors

no code implementations26 Jun 2015 Gregory J. Puleo, Olgica Milenkovic

We consider a generalized version of the correlation clustering problem, defined as follows.

Correlation Clustering with Constrained Cluster Sizes and Extended Weights Bounds

no code implementations3 Nov 2014 Gregory J. Puleo, Olgica Milenkovic

We consider the problem of correlation clustering on graphs with constraints on both the cluster sizes and the positive and negative weights of edges.

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