Vaggos Chatziafratis | DeepAI

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∙ 12/24/2022

Triplet Reconstruction and all other Phylogenetic CSPs are Approximation Resistant

We study the natural problem of Triplet Reconstruction (also Rooted Trip...

0 Vaggos Chatziafratis, et al. ∙

∙ 10/11/2022

On Scrambling Phenomena for Randomly Initialized Recurrent Networks

Recurrent Neural Networks (RNNs) frequently exhibit complicated dynamics...

0 Vaggos Chatziafratis, et al. ∙

∙ 08/03/2022

Efficiently Computing Nash Equilibria in Adversarial Team Markov Games

Computing Nash equilibrium policies is a central problem in multi-agent ...

0 Fivos Kalogiannis, et al. ∙

∙ 10/19/2021

Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky's Theorem

Given a target function f, how large must a neural network be in order t...

0 Clayton Sanford, et al. ∙

∙ 02/23/2021

Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUT

In this paper, we study a number of well-known combinatorial optimizatio...

0 Vaggos Chatziafratis, et al. ∙

∙ 01/26/2021

Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering

Recently, Hierarchical Clustering (HC) has been considered through the l...

0 Danny Vainstein, et al. ∙

∙ 10/04/2020

Inapproximability for Local Correlation Clustering and Dissimilarity Hierarchical Clustering

We present hardness of approximation results for Correlation Clustering ...

0 Vaggos Chatziafratis, et al. ∙

∙ 10/01/2020

From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering

Similarity-based Hierarchical Clustering (HC) is a classical unsupervise...

4 Ines Chami, et al. ∙

∙ 03/02/2020

Better Depth-Width Trade-offs for Neural Networks through the lens of Dynamical Systems

The expressivity of neural networks as a function of their depth, width ...

0 Vaggos Chatziafratis, et al. ∙

∙ 12/15/2019

Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection

Hierarchical Clustering is an unsupervised data analysis method which ha...

0 Sara Ahmadian, et al. ∙

∙ 12/09/2019

Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem

Understanding the representational power of Deep Neural Networks (DNNs) ...

0 Vaggos Chatziafratis, et al. ∙

∙ 11/29/2019

Adversarially Robust Low Dimensional Representations

Adversarial or test time robustness measures the susceptibility of a mac...

0 Pranjal Awasthi, et al. ∙

∙ 12/27/2018

Hierarchical Clustering for Euclidean Data

Recent works on Hierarchical Clustering (HC), a well-studied problem in ...

0 Moses Charikar, et al. ∙

∙ 10/19/2018

Bilu-Linial stability, certified algorithms and the Independent Set problem

We study the notion of Bilu-Linial stability in the context of Independe...

0 Haris Angelidakis, et al. ∙

∙ 08/07/2018

Hierarchical Clustering better than Average-Linkage

Hierarchical Clustering (HC) is a widely studied problem in exploratory ...

0 Moses Charikar, et al. ∙

∙ 07/03/2018

On the Computational Power of Online Gradient Descent

We prove that the evolution of weight vectors in online gradient descent...

0 Vaggos Chatziafratis, et al. ∙

∙ 05/24/2018

Hierarchical Clustering with Structural Constraints

Hierarchical clustering is a popular unsupervised data analysis method. ...

0 Vaggos Chatziafratis, et al. ∙

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