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Found 14 papers, 1 papers with code
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams
Our results show that the proposed partner-aware strategy outperforms other known methods, and our human subject studies suggest humans prefer to collaborate with AI agents implementing our partner-aware strategy.
Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
Further, the expected convergence rate decays exponentially with the quality of the trust observations between agents.
Optimization and Control Robotics Systems and Control Signal Processing Systems and Control
Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes
In particular, when the number of processing elements $P$ that can perform SSC decoding operations in parallel is limited, as is the case in practice, the latency of SSC decoding is $O\left(N^{1-1/\mu}+\frac{N}{P}\log_2\log_2\frac{N}{P}\right)$, where $N$ is the block length of the code and $\mu$ is the scaling exponent of the channel.
Information Theory Information Theory
Bayesian Algorithms for Decentralized Stochastic Bandits
Specifically, we study an information assimilation algorithm that can be combined with existing Bayesian algorithms, and using this, we propose a decentralized Thompson Sampling algorithm and decentralized Bayes-UCB algorithm.
Construction of Polar Codes with Reinforcement Learning
This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement learning techniques.
Exploiting Local and Cloud Sensor Fusion in Intermittently Connected Sensor Networks
We refer to this hybrid communication scheme as a cloud-cluster architecture.
Distributed Convex Optimization With Limited Communications
In this paper, a distributed convex optimization algorithm, termed \emph{distributed coordinate dual averaging} (DCDA) algorithm, is proposed.
Sliding Bidirectional Recurrent Neural Networks for Sequence Detection in Communication Systems
The design and analysis of communication systems typically rely on the development of mathematical models that describe the underlying communication channel.
Deep Learning for Joint Source-Channel Coding of Text
We consider the problem of joint source and channel coding of structured data such as natural language over a noisy channel.
Neural Network Detection of Data Sequences in Communication Systems
We consider detection based on deep learning, and show it is possible to train detectors that perform well without any knowledge of the underlying channel models.
Detection Algorithms for Communication Systems Using Deep Learning
The design and analysis of communication systems typically rely on the development of mathematical models that describe the underlying communication channel, which dictates the relationship between the transmitted and the received signals.
A Novel Experimental Platform for In-Vessel Multi-Chemical Molecular Communications
This work presents a new multi-chemical experimental platform for molecular communication where the transmitter can release different chemicals.
On the Total-Power Capacity of Regular-LDPC Codes with Iterative Message-Passing Decoders
We analyze scaling behavior under two VLSI complexity models of decoding.
Information Theory Information Theory
Exact and Stable Covariance Estimation from Quadratic Sampling via Convex Programming
Our method admits universally accurate covariance estimation in the absence of noise, as soon as the number of measurements exceeds the information theoretic limits.
