Search Results for author: Pramod Viswanath

Found 40 papers, 17 papers with code

DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning

no code implementations14 Feb 2024 S Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim, Sewoong Oh, Pramod Viswanath

Polar codes, developed on the foundation of Arikan's polarization kernel, represent a breakthrough in coding theory and have emerged as the state-of-the-art error-correction-code in short-to-medium block length regimes.

ZeroSwap: Data-driven Optimal Market Making in DeFi

no code implementations13 Oct 2023 Viraj Nadkarni, Jiachen Hu, Ranvir Rana, Chi Jin, Sanjeev Kulkarni, Pramod Viswanath

This ensures that the market maker balances losses to informed traders with profits from noise traders.

Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes

no code implementations16 Jan 2023 Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

Next, we derive the soft-decision based version of our algorithm, called soft-subRPA, that not only improves upon the performance of subRPA but also enables a differentiable decoding algorithm.

CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family

1 code implementation1 Oct 2022 S Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath

We design a principled curriculum, guided by information-theoretic insights, to train CRISP and show that it outperforms the successive-cancellation (SC) decoder and attains near-optimal reliability performance on the Polar(32, 16) and Polar(64, 22) codes.

TinyTurbo: Efficient Turbo Decoders on Edge

1 code implementation30 Sep 2022 S Ashwin Hebbar, Rajesh K Mishra, Sravan Kumar Ankireddy, Ashok V Makkuva, Hyeji Kim, Pramod Viswanath

In this paper, we introduce a neural-augmented decoder for Turbo codes called TINYTURBO .

KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning

1 code implementation29 Aug 2021 Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

In this paper, we construct KO codes, a computationaly efficient family of deep-learning driven (encoder, decoder) pairs that outperform the state-of-the-art reliability performance on the standardized AWGN channel.

Benchmarking

Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding

no code implementations2 Feb 2021 Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

To lower the complexity of our decoding algorithm, referred to as subRPA in this paper, we investigate different ways for pruning the projections.

Information Theory Information Theory

Enriching Word Embeddings with Temporal and Spatial Information

1 code implementation CONLL 2020 Hongyu Gong, Suma Bhat, Pramod Viswanath

The meaning of a word is closely linked to sociocultural factors that can change over time and location, resulting in corresponding meaning changes.

Word Embeddings

Deepcode and Modulo-SK are Designed for Different Settings

no code implementations18 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.

Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels

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.

Practical Low Latency Proof of Work Consensus

2 code implementations25 Sep 2019 Lei Yang, Vivek Bagaria, Gerui Wang, Mohammad Alizadeh, David Tse, Giulia Fanti, Pramod Viswanath

Bitcoin is the first fully-decentralized permissionless blockchain protocol to achieve a high level of security, but at the expense of poor throughput and latency.

Distributed, Parallel, and Cluster Computing Cryptography and Security Networking and Internet Architecture

Learning in Gated Neural Networks

no code implementations6 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.

DeepTurbo: Deep Turbo Decoder

1 code implementation6 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.

Context-Sensitive Malicious Spelling Error Correction

no code implementations23 Jan 2019 Hongyu Gong, Yuchen Li, Suma Bhat, Pramod Viswanath

Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection.

Spam detection Spelling Correction +1

LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks

1 code implementation30 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.

Learning One-hidden-layer Neural Networks under General Input Distributions

no code implementations9 Oct 2018 Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath

Significant advances have been made recently on training neural networks, where the main challenge is in solving an optimization problem with abundant critical points.

Preposition Sense Disambiguation and Representation

1 code implementation EMNLP 2018 Hongyu Gong, Jiaqi Mu, Suma Bhat, Pramod Viswanath

Prepositions are highly polysemous, and their variegated senses encode significant semantic information.

PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously

no code implementations27 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

Deepcode: Feedback Codes via Deep Learning

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.

Communication Algorithms via Deep Learning

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).

Embedding Syntax and Semantics of Prepositions via Tensor Decomposition

no code implementations NAACL 2018 Hongyu Gong, Suma Bhat, Pramod Viswanath

Prepositions are among the most frequent words in English and play complex roles in the syntax and semantics of sentences.

Tensor Decomposition

Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms

no code implementations21 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.

Ensemble Learning

Deanonymization in the Bitcoin P2P Network

1 code implementation NeurIPS 2017 Giulia Fanti, Pramod Viswanath

Recent attacks on Bitcoin's peer-to-peer (P2P) network demonstrated that its transaction-flooding protocols, which are used to ensure network consistency, may enable user deanonymization---the linkage of a user's IP address with her pseudonym in the Bitcoin network.

Estimating Mutual Information for Discrete-Continuous Mixtures

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.

Clustering Mutual Information Estimation

MORSE: Semantic-ally Drive-n MORpheme SEgment-er

no code implementations ACL 2017 Tarek Sakakini, Suma Bhat, Pramod Viswanath

We present in this paper a novel framework for morpheme segmentation which uses the morpho-syntactic regularities preserved by word representations, in addition to orthographic features, to segment words into morphemes.

Benchmarking

Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology

no code implementations7 Feb 2017 Tarek Sakakini, Suma Bhat, Pramod Viswanath

We present an unsupervised and language-agnostic method for learning root-and-pattern morphology in Semitic languages.

All-but-the-Top: Simple and Effective Postprocessing for Word Representations

4 code implementations ICLR 2018 Jiaqi Mu, Suma Bhat, Pramod Viswanath

The postprocessing is empirically validated on a variety of lexical-level intrinsic tasks (word similarity, concept categorization, word analogy) and sentence-level tasks (semantic textural similarity and { text classification}) on multiple datasets and with a variety of representation methods and hyperparameter choices in multiple languages; in each case, the processed representations are consistently better than the original ones.

General Classification Sentence +4

Prepositions in Context

no code implementations5 Feb 2017 Hongyu Gong, Jiaqi Mu, Suma Bhat, Pramod Viswanath

Prepositions are highly polysemous, and their variegated senses encode significant semantic information.

Clustering

Dandelion: Redesigning the Bitcoin Network for Anonymity

2 code implementations16 Jan 2017 Shaileshh Bojja Venkatakrishnan, Giulia Fanti, Pramod Viswanath

We propose a simple networking policy called Dandelion, which achieves nearly-optimal anonymity guarantees at minimal cost to the network's utility.

Cryptography and Security Information Theory Information Theory

Geometry of Compositionality

1 code implementation29 Nov 2016 Hongyu Gong, Suma Bhat, Pramod Viswanath

This paper proposes a simple test for compositionality (i. e., literal usage) of a word or phrase in a context-specific way.

Word Embeddings

Geometry of Polysemy

no code implementations24 Oct 2016 Jiaqi Mu, Suma Bhat, Pramod Viswanath

Vector representations of words have heralded a transformational approach to classical problems in NLP; the most popular example is word2vec.

Clustering Sentence

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation

no code implementations NeurIPS 2016 Weihao Gao, Sewoong Oh, Pramod Viswanath

In this paper, we combine both these approaches to design new estimators of entropy and mutual information that outperform state of the art methods.

Demystifying Fixed k-Nearest Neighbor Information Estimators

1 code implementation11 Apr 2016 Weihao Gao, Sewoong Oh, Pramod Viswanath

In this paper we demonstrate that the estimator is consistent and also identify an upper bound on the rate of convergence of the bias as a function of number of samples.

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications

no code implementations10 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.

Secure Multi-party Differential Privacy

no code implementations NeurIPS 2015 Peter Kairouz, Sewoong Oh, Pramod Viswanath

In this setting, each party is interested in computing a function on its private bit and all the other parties' bits.

Spy vs. Spy: Rumor Source Obfuscation

no code implementations29 Dec 2014 Giulia Fanti, Peter Kairouz, Sewoong Oh, Pramod Viswanath

Whether for fear of judgment or personal endangerment, it is crucial to keep anonymous the identity of the user who initially posted a sensitive message.

The Composition Theorem for Differential Privacy

no code implementations4 Nov 2013 Peter Kairouz, Sewoong Oh, Pramod Viswanath

Sequential querying of differentially private mechanisms degrades the overall privacy level.

Data Structures and Algorithms Cryptography and Security Information Theory Information Theory

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