Sriram Vishwanath

research

∙ 04/10/2023

iDML: Incentivized Decentralized Machine Learning

With the rising emergence of decentralized and opportunistic approaches ...

0 Haoxiang Yu, et al. ∙

research

∙ 10/23/2022

A Control Theoretic Approach to Infrastructure-Centric Blockchain Tokenomics

There are a multitude of Blockchain-based physical infrastructure system...

0 Oguzhan Akcin, et al. ∙

research

∙ 07/12/2022

Achieving Almost All Blockchain Functionalities with Polylogarithmic Storage

In current blockchain systems, full nodes that perform all of the availa...

0 Parikshit Hegde, et al. ∙

research

∙ 06/21/2022

Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learning

Contrastive self-supervised learning methods learn to map data points su...

0 Ali Lotfi Rezaabad, et al. ∙

research

∙ 12/21/2021

BlockReduce – Scaling Proof-of-Work Blockchains

This paper introduces BlockReduce, a Proof-of-Work (PoW) based blockchai...

0 Yanni Georghiades, et al. ∙

research

∙ 03/02/2021

Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization

Accelerated multi-coil magnetic resonance imaging reconstruction has see...

0 Marius Arvinte, et al. ∙

research

∙ 12/24/2020

Network Design for Social Welfare

In this paper, we consider the problem of network design on network game...

0 Abhishek Shende, et al. ∙

research

∙ 12/23/2020

EQ-Net: A Unified Deep Learning Framework for Log-Likelihood Ratio Estimation and Quantization

In this work, we introduce EQ-Net: the first holistic framework that sol...

0 Marius Arvinte, et al. ∙

research

∙ 10/31/2020

Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational Inference

Efficient modeling of relational data arising in physical, social, and i...

0 Ali Lotfi Rezaabad, et al. ∙

research

∙ 07/09/2020

Long Short-Term Memory Spiking Networks and Their Applications

Recent advances in event-based neuromorphic systems have resulted in sig...

0 Ali Lotfi Rezaabad, et al. ∙

research

∙ 06/26/2020

Interpretable Factorization for Neural Network ECG Models

The ability of deep learning (DL) to improve the practice of medicine an...

0 Christopher Snyder, et al. ∙

research

∙ 06/05/2020

Robust Face Verification via Disentangled Representations

We introduce a robust algorithm for face verification, i.e., deciding wh...

0 Marius Arvinte, et al. ∙

research

∙ 03/25/2020

Deep Networks as Logical Circuits: Generalization and Interpretation

Not only are Deep Neural Networks (DNNs) black box models, but also we f...

15 Christopher Snyder, et al. ∙

research

∙ 02/28/2020

Detecting Patch Adversarial Attacks with Image Residuals

We introduce an adversarial sample detection algorithm based on image re...

0 Marius Arvinte, et al. ∙

research

∙ 02/07/2020

Stability and Scalability of Blockchain Systems

The blockchain paradigm provides a mechanism for content dissemination a...

0 Aditya Gopalan, et al. ∙

research

∙ 01/27/2020

Achieving Multi-Port Memory Performance on Single-Port Memory with Coding Techniques

Many performance critical systems today must rely on performance enhance...

0 Hardik Jain, et al. ∙

research

∙ 01/16/2020

Sequential decomposition of graphon mean field games

In this paper, we present a sequential decomposition algorithm to comput...

0 Deepanshu Vasal, et al. ∙

research

∙ 12/21/2019

Learning Representations by Maximizing Mutual Information in Variational Autoencoder

Variational autoencoders (VAE) have ushered in a new era of unsupervised...

0 Ali Lotfi Rezaabad, et al. ∙

research

∙ 06/18/2019

Deep Learning-Based Quantization of L-Values for Gray-Coded Modulation

In this work, a deep learning-based quantization scheme for log-likeliho...

0 Marius Arvinte, et al. ∙

research

∙ 03/11/2019

Deep Log-Likelihood Ratio Quantization

In this work, a deep learning-based method for log-likelihood ratio (LLR...

0 Marius Arvinte, et al. ∙

research

∙ 01/31/2019

HashCore: Proof-of-Work Functions for General Purpose Processors

Over the past five years, the reward associated with mining Proof-of-Wor...

0 Yanni Georghiades, et al. ∙

research

∙ 11/05/2018

Generalization Bounds for Neural Networks: Kernels, Symmetry, and Sample Compression

Though Deep Neural Networks (DNNs) are widely celebrated for their pract...

0 Christopher Snyder, et al. ∙

research

∙ 10/28/2018

Experimental Design for Cost-Aware Learning of Causal Graphs

We consider the minimum cost intervention design problem: Given the esse...

6 Erik M. Lindgren, et al. ∙

research

∙ 07/26/2018

Entropic Latent Variable Discovery

We consider the problem of discovering the simplest latent variable that...

2 Murat Kocaoglu, et al. ∙

research

∙ 06/17/2018

Compressed Sensing with Deep Image Prior and Learned Regularization

We propose a novel method for compressed sensing recovery using untraine...

10 David Van Veen, et al. ∙

research

∙ 01/23/2018

On the Key Generation Rate of Physically Unclonable Functions

In this paper, an algebraic binning based coding scheme and its associat...

0 Yitao Chen, et al. ∙

research

∙ 09/06/2017

CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training

We propose an adversarial training procedure for learning a causal impli...

0 Murat Kocaoglu, et al. ∙

research

∙ 03/08/2017

Cost-Optimal Learning of Causal Graphs

We consider the problem of learning a causal graph over a set of variabl...

0 Murat Kocaoglu, et al. ∙

research

∙ 01/28/2017

Entropic Causality and Greedy Minimum Entropy Coupling

We study the problem of identifying the causal relationship between two ...

0 Murat Kocaoglu, et al. ∙

research

∙ 11/12/2016

Entropic Causal Inference

We consider the problem of identifying the causal direction between two ...

0 Murat Kocaoglu, et al. ∙

research

∙ 10/30/2015

Learning Causal Graphs with Small Interventions

We consider the problem of learning causal networks with interventions, ...

0 Karthikeyan Shanmugam, et al. ∙

research

∙ 09/22/2011

Sparse Online Low-Rank Projection and Outlier Rejection (SOLO) for 3-D Rigid-Body Motion Registration

Motivated by an emerging theory of robust low-rank matrix representation...

0 Chris Slaughter, et al. ∙

Sriram Vishwanath

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