Search Results for author: Payam Delgosha

Found 6 papers, 1 papers with code

MM-GATBT: Enriching Multimodal Representation Using Graph Attention Network

1 code implementation NAACL (ACL) 2022 Seung Byum Seo, Hyoungwook Nam, Payam Delgosha

While there have been advances in Natural Language Processing (NLP), their success is mainly gained by applying a self-attention mechanism into single or multi-modalities.

Graph Attention Graph Representation Learning

Binary Classification Under $\ell_0$ Attacks for General Noise Distribution

no code implementations9 Mar 2022 Payam Delgosha, Hamed Hassani, Ramtin Pedarsani

We introduce a classification method which employs a nonlinear component called truncation, and show in an asymptotic scenario, as long as the adversary is restricted to perturb no more than $\sqrt{d}$ data samples, we can almost achieve the optimal classification error in the absence of the adversary, i. e. we can completely neutralize adversary's effect.


Efficient and Robust Classification for Sparse Attacks

no code implementations23 Jan 2022 Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani

In the past two decades we have seen the popularity of neural networks increase in conjunction with their classification accuracy.

Classification Malware Detection +1

Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model

no code implementations5 Apr 2021 Payam Delgosha, Hamed Hassani, Ramtin Pedarsani

Under the assumption that data is distributed according to the Gaussian mixture model, our goal is to characterize the optimal robust classifier and the corresponding robust classification error as well as a variety of trade-offs between robustness, accuracy, and the adversary's budget.

Classification General Classification +1

Deep Switch Networks for Generating Discrete Data and Language

no code implementations14 Mar 2019 Payam Delgosha, Naveen Goela

Unlike deconvolution networks which generate continuous-valued data and which consist of upsampling filters and reverse pooling layers, multilayer switch networks are composed of adaptive switches which model conditional distributions of discrete random variables.

Time Series Analysis

Randomized Algorithms for Comparison-based Search

no code implementations NeurIPS 2011 Dominique Tschopp, Suhas Diggavi, Payam Delgosha, Soheil Mohajer

This paper addresses the problem of finding the nearest neighbor (or one of the $R$-nearest neighbors) of a query object $q$ in a database of $n$ objects, when we can only use a comparison oracle.


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