
ACeD: Scalable Data Availability Oracle
A popular method in practice offloads computation and storage in blockch...
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The Checkpointed Longest Chain: Userdependent Adaptivity and Finality
Longestchain protocols such as the one invented by Nakamoto for Bitcoin...
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PoSAT: ProofofWork Availability andUnpredictability, without the Work
An important feature of ProofofWork (PoW) blockchains is full dynamic ...
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BFT Protocol Forensics
Byzantine faulttolerant (BFT) protocols allow a group of replicas to co...
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Deepcode and ModuloSK are Designed for Different Settings
We respond to [1] which claimed that "ModuloSK scheme outperforms Deepc...
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Perigee: Efficient PeertoPeer Network Design for Blockchains
A key performance metric in blockchains is the latency between when a tr...
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Everything is a Race and Nakamoto Always Wins
Nakamoto invented the longest chain protocol, and claimed its security b...
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Free2Shard: Adaptiveadversaryresistant sharding via Dynamic Self Allocation
Propelled by the growth of largescale blockchain deployments, much rece...
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CMIGAN : Estimation of Conditional Mutual Information using MinMax formulation
Estimation of information theoretic quantities such as mutual informatio...
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Turbo Autoencoder: Deep learning based channel codes for pointtopoint communication channels
Designing codes that combat the noise in a communication medium has rema...
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ProofofStake Longest Chain Protocols Revisited
The Nakamoto longest chain protocol has served Bitcoin well in its decad...
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Coded Merkle Tree: Solving Data Availability Attacks in Blockchains
In this paper, we propose coded Merkle tree (CMT), a novel hash accumula...
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Improving Federated Learning Personalization via Model Agnostic Meta Learning
Federated Learning (FL) refers to learning a high quality global model b...
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Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples
Deep learning classifiers are known to be vulnerable to adversarial exam...
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Coded State Machine  Scaling State Machine Execution under Byzantine Faults
We introduce an informationtheoretic framework, named Coded State Machi...
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Learning in Gated Neural Networks
Gating is a key feature in modern neural networks including LSTMs, GRUs ...
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CCMI : Classifier based Conditional Mutual Information Estimation
Conditional Mutual Information (CMI) is a measure of conditional depende...
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Dropping Pixels for Adversarial Robustness
Deep neural networks are vulnerable against adversarial examples. In thi...
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DeepTurbo: Deep Turbo Decoder
Presentday communication systems routinely use codes that approach the ...
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LEARN Codes: Inventing Lowlatency Codes via Recurrent Neural Networks
Designing channel codes under low latency constraints is one of the most...
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Estimators for Multivariate Information Measures in General Probability Spaces
Information theoretic quantities play an important role in various setti...
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Deconstructing the Blockchain to Approach Physical Limits
Transaction throughput, confirmation latency and confirmation reliabilit...
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PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously
Today's blockchains do not scale in a meaningful sense. As more nodes jo...
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ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
Generative Adversarial networks (GANs) have obtained remarkable success ...
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Deepcode: Feedback Codes via Deep Learning
The design of codes for communicating reliably over a statistically well...
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Mimic and Classify : A metaalgorithm for Conditional Independence Testing
Given independent samples generated from the joint distribution p(x,y,z)...
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Communication Algorithms via Deep Learning
Coding theory is a central discipline underpinning wireline and wireless...
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Globally Consistent Algorithms for Mixture of Experts
MixtureofExperts (MoE) is a widely popular neural network architecture...
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Potential Conditional Mutual Information: Estimators, Properties and Applications
The conditional mutual information I(X;YZ) measures the average informa...
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Discovering Potential Correlations via Hypercontractivity
Discovering a correlation from one variable to another variable is of fu...
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Learning Temporal Dependence from TimeSeries Data with Latent Variables
We consider the setting where a collection of time series, modeled as ra...
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Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications
We conduct an axiomatic study of the problem of estimating the strength ...
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Sreeram Kannan
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