Hemant Tyagi | DeepAI

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∙ 03/27/2023

Learning linear dynamical systems under convex constraints

We consider the problem of identification of linear dynamical systems fr...

0 Hemant Tyagi, et al. ∙

∙ 07/04/2022

Dynamic Ranking and Translation Synchronization

In many applications, such as sport tournaments or recommendation system...

0 Ernesto Araya, et al. ∙

∙ 05/24/2022

Minimax Optimal Clustering of Bipartite Graphs with a Generalized Power Method

Clustering bipartite graphs is a fundamental task in network analysis. I...

0 Guillaume Braun, et al. ∙

∙ 04/08/2022

Seeded graph matching for the correlated Wigner model via the projected power method

In the graph matching problem we observe two graphs G,H and the goal is ...

0 Ernesto Araya, et al. ∙

∙ 12/20/2021

An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guarantees

Real-world networks often come with side information that can help to im...

0 Guillaume Braun, et al. ∙

∙ 12/02/2021

Recovering Hölder smooth functions from noisy modulo samples

In signal processing, several applications involve the recovery of a fun...

0 Michaël Fanuel, et al. ∙

∙ 09/28/2021

Dynamic Ranking with the BTL Model: A Nearest Neighbor based Rank Centrality Method

Many applications such as recommendation systems or sports tournaments i...

0 Eglantine Karlé, et al. ∙

∙ 03/04/2021

Clustering multilayer graphs with missing nodes

Relationship between agents can be conveniently represented by graphs. W...

0 Guillaume Braun, et al. ∙

∙ 12/29/2020

An extension of the angular synchronization problem to the heterogeneous setting

Given an undirected measurement graph G = ([n], E), the classical angula...

4 Mihai Cucuringu, et al. ∙

∙ 11/03/2020

Regularized spectral methods for clustering signed networks

We study the problem of k-way clustering in signed graphs. Considerable ...

6 Mihai Cucuringu, et al. ∙

∙ 09/10/2020

Error analysis for denoising smooth modulo signals on a graph

In many applications, we are given access to noisy modulo samples of a s...

0 Hemant Tyagi, et al. ∙

∙ 09/10/2020

Denoising modulo samples: k-NN regression and tightness of SDP relaxation

Many modern applications involve the acquisition of noisy modulo samples...

0 Michaël Fanuel, et al. ∙

∙ 06/06/2019

Ranking and synchronization from pairwise measurements via SVD

Given a measurement graph G= (V,E) and an unknown signal r ∈R^n, we inve...

0 Alexandre d'Aspremont, et al. ∙

∙ 04/18/2019

SPONGE: A generalized eigenproblem for clustering signed networks

We introduce a principled and theoretically sound spectral method for k-...

0 Mihai Cucuringu, et al. ∙

∙ 07/08/2018

Multi-kernel unmixing and super-resolution using the Modified Matrix Pencil method

Consider L groups of point sources or spike trains, with the l^th group ...

0 Stéphane Chrétien, et al. ∙

∙ 04/04/2018

Sparse non-negative super-resolution - simplified and stabilised

The convolution of a discrete measure, x=∑_i=1^ka_iδ_t_i, with a local w...

0 Armin Eftekhari, et al. ∙

∙ 03/09/2018

Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping

Consider an unknown smooth function f: [0,1]^d →R, and say we are given ...

0 Mihai Cucuringu, et al. ∙

∙ 10/27/2017

On denoising modulo 1 samples of a function

Consider an unknown smooth function f: [0,1] →R, and say we are given n ...

0 Mihai Cucuringu, et al. ∙

∙ 05/02/2016

Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions

A function f: R^d →R is a Sparse Additive Model (SPAM), if it is of the ...

0 Hemant Tyagi, et al. ∙

∙ 04/18/2016

Learning Sparse Additive Models with Interactions in High Dimensions

A function f: R^d →R is referred to as a Sparse Additive Model (SPAM), i...

0 Hemant Tyagi, et al. ∙

∙ 12/01/2013

Stochastic continuum armed bandit problem of few linear parameters in high dimensions

We consider a stochastic continuum armed bandit problem where the arms a...

0 Hemant Tyagi, et al. ∙

∙ 10/07/2013

Learning Non-Parametric Basis Independent Models from Point Queries via Low-Rank Methods

We consider the problem of learning multi-ridge functions of the form f(...

0 Hemant Tyagi, et al. ∙

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