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no code implementations • 18 Aug 2020 • Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

DeepCode is designed and evaluated for the AWGN channel with (potentially delayed) uncoded output feedback.

no code implementations • 17 May 2020 • Arnab Kumar Mondal, Arnab Bhattacharya, Sudipto Mukherjee, Prathosh AP, Sreeram Kannan, Himanshu Asnani

Estimation of information theoretic quantities such as mutual information and its conditional variant has drawn interest in recent times owing to their multifaceted applications.

1 code implementation • NeurIPS 2019 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Designing codes that combat the noise in a communication medium has remained a significant area of research in information theory as well as wireless communications.

2 code implementations • 27 Sep 2019 • Yihan Jiang, Jakub Konečný, Keith Rush, Sreeram Kannan

We present FL as a natural source of practical applications for MAML algorithms, and make the following observations.

no code implementations • 28 Jul 2019 • Hossein Hosseini, Sreeram Kannan, Radha Poovendran

In this paper, we first develop a classifier-based adaptation of the statistical test method and show that it improves the detection performance.

no code implementations • 6 Jun 2019 • Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath

Gating is a key feature in modern neural networks including LSTMs, GRUs and sparsely-gated deep neural networks.

no code implementations • 5 Jun 2019 • Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan

Conditional Mutual Information (CMI) is a measure of conditional dependence between random variables X and Y, given another random variable Z.

no code implementations • 1 May 2019 • Hossein Hosseini, Sreeram Kannan, Radha Poovendran

Deep neural networks are vulnerable against adversarial examples.

1 code implementation • 6 Mar 2019 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

We focus on Turbo codes and propose DeepTurbo, a novel deep learning based architecture for Turbo decoding.

1 code implementation • 14 Feb 2019 • Shunfu Mao, Yihan Jiang, Edwin Basil Mathew, Sreeram Kannan

High throughput sequencing of RNA (RNA-Seq) can provide us with millions of short fragments of RNA transcripts from a sample.

1 code implementation • 30 Nov 2018 • Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Designing channel codes under low-latency constraints is one of the most demanding requirements in 5G standards.

no code implementations • 27 Sep 2018 • Songze Li, Mingchao Yu, Chien-Sheng Yang, A. Salman Avestimehr, Sreeram Kannan, Pramod Viswanath

In particular, we propose PolyShard: ``polynomially coded sharding'' scheme that achieves information-theoretic upper bounds on the efficiency of the storage, system throughput, as well as on trust, thus enabling a truly scalable system.

Cryptography and Security Distributed, Parallel, and Cluster Computing Information Theory Information Theory

7 code implementations • 10 Sep 2018 • Sudipto Mukherjee, Himanshu Asnani, Eugene Lin, Sreeram Kannan

While one can potentially exploit the latent-space back-projection in GANs to cluster, we demonstrate that the cluster structure is not retained in the GAN latent space.

1 code implementation • NeurIPS 2018 • Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

The design of codes for communicating reliably over a statistically well defined channel is an important endeavor involving deep mathematical research and wide-ranging practical applications.

1 code implementation • 25 Jun 2018 • Rajat Sen, Karthikeyan Shanmugam, Himanshu Asnani, Arman Rahimzamani, Sreeram Kannan

Given independent samples generated from the joint distribution $p(\mathbf{x},\mathbf{y},\mathbf{z})$, we study the problem of Conditional Independence (CI-Testing), i. e., whether the joint equals the CI distribution $p^{CI}(\mathbf{x},\mathbf{y},\mathbf{z})= p(\mathbf{z}) p(\mathbf{y}|\mathbf{z})p(\mathbf{x}|\mathbf{z})$ or not.

3 code implementations • ICLR 2018 • Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

We show that creatively designed and trained RNN architectures can decode well known sequential codes such as the convolutional and turbo codes with close to optimal performance on the additive white Gaussian noise (AWGN) channel, which itself is achieved by breakthrough algorithms of our times (Viterbi and BCJR decoders, representing dynamic programing and forward-backward algorithms).

no code implementations • 21 Feb 2018 • Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath

Once the experts are known, the recovery of gating parameters still requires an EM algorithm; however, we show that the EM algorithm for this simplified problem, unlike the joint EM algorithm, converges to the true parameters.

no code implementations • 13 Oct 2017 • Arman Rahimzamani, Sreeram Kannan

We define the potential conditional mutual information as the conditional mutual information calculated with a modified joint distribution p_{Y|X, Z} q_{X, Z}, where q_{X, Z} is a potential distribution, fixed airport.

1 code implementation • NeurIPS 2017 • Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

We provide numerical experiments suggesting superiority of the proposed estimator compared to other heuristics of adding small continuous noise to all the samples and applying standard estimators tailored for purely continuous variables, and quantizing the samples and applying standard estimators tailored for purely discrete variables.

no code implementations • NeurIPS 2017 • Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

Discovering a correlation from one variable to another variable is of fundamental scientific and practical interest.

no code implementations • 13 Mar 2017 • Hossein Hosseini, Yize Chen, Sreeram Kannan, Baosen Zhang, Radha Poovendran

Advances in Machine Learning (ML) have led to its adoption as an integral component in many applications, including banking, medical diagnosis, and driverless cars.

no code implementations • 27 Feb 2017 • Hossein Hosseini, Sreeram Kannan, Baosen Zhang, Radha Poovendran

In this paper, we propose an attack on the Perspective toxic detection system based on the adversarial examples.

no code implementations • 27 Aug 2016 • Hossein Hosseini, Sreeram Kannan, Baosen Zhang, Radha Poovendran

We consider the setting where a collection of time series, modeled as random processes, evolve in a causal manner, and one is interested in learning the graph governing the relationships of these processes.

no code implementations • 10 Feb 2016 • Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

We conduct an axiomatic study of the problem of estimating the strength of a known causal relationship between a pair of variables.

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