Search Results for author: Shlomo Shamai

Found 18 papers, 3 papers with code

Successive Refinement in Large-Scale Computation: Advancing Model Inference Applications

no code implementations11 Feb 2024 Homa Esfahanizadeh, Alejandro Cohen, Shlomo Shamai, Muriel Medard

This innovation notably enhances the deadline-based systems, as if a computational job is terminated due to time constraints, an approximate version of the final result can still be generated.

Decision Making

Cross-Validation Conformal Risk Control

no code implementations22 Jan 2024 Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Shlomo Shamai

CV-CRC is proved to offer theoretical guarantees on the average risk of the set predictor.

Conformal Prediction

Deep Learning Assisted Multiuser MIMO Load Modulated Systems for Enhanced Downlink mmWave Communications

no code implementations8 Nov 2023 Ercong Yu, Jinle Zhu, Qiang Li, Zilong Liu, Hongyang Chen, Shlomo Shamai, H. Vincent Poor

The existing precoding algorithm for downlink MU-LMA relies on a sub-array structured (SAS) transmitter which may suffer from decreased degrees of freedom and complex system configuration.

Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction

1 code implementation15 Feb 2023 Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Petar Popovski, Shlomo Shamai

The dynamic scheduling of ultra-reliable and low-latency traffic (URLLC) in the uplink can significantly enhance the efficiency of coexisting services, such as enhanced mobile broadband (eMBB) devices, by only allocating resources when necessary.

Conformal Prediction Scheduling

Calibrating AI Models for Wireless Communications via Conformal Prediction

no code implementations15 Dec 2022 Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Shlomo Shamai

This paper investigates the application of conformal prediction as a general framework to obtain AI models that produce decisions with formal calibration guarantees.

Conformal Prediction

Calibrating AI Models for Few-Shot Demodulation via Conformal Prediction

no code implementations10 Oct 2022 Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Shlomo Shamai

We propose to leverage the conformal prediction framework to obtain data-driven set predictions whose calibration properties hold irrespective of the data distribution.

Conformal Prediction

Robust Design of Rate-Splitting Multiple Access With Imperfect CSI for Cell-Free MIMO Systems

no code implementations7 Mar 2022 DaeSung Yu, Seok-Hwan Park, Osvaldo Simeone, Shlomo Shamai

Rate-Splitting Multiple Access (RSMA) for multi-user downlink operates by splitting the message for each user equipment (UE) into a private message and a set of common messages, which are simultaneously transmitted by means of superposition coding.

Robust Design

A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman Divergence

no code implementations23 Feb 2022 Alex Dytso, Mario Goldenbaum, H. Vincent Poor, Shlomo Shamai

A common way of characterizing minimax estimators in point estimation is by moving the problem into the Bayesian estimation domain and finding a least favorable prior distribution.

Dimensionality Reduction

Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization

1 code implementation2 Aug 2021 Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Shlomo Shamai

Bayesian active meta-learning is seen in experiments to significantly reduce the number of frames required to obtain efficient adaptation procedure for new frames.

Few-Shot Learning Variational Inference

A General Derivative Identity for the Conditional Mean Estimator in Gaussian Noise and Some Applications

no code implementations5 Apr 2021 Alex Dytso, H. Vincent Poor, Shlomo Shamai

In the second part of the paper, via various choices of ${\bf U}$, the new identity is used to generalize many of the known identities and derive some new ones.

Collaborative Cloud and Edge Mobile Computing in C-RAN Systems with Minimal End-to-End Latency

no code implementations30 Mar 2021 Seok-Hwan Park, Seongah Jeong, Jinyeop Na, Osvaldo Simeone, Shlomo Shamai

Mobile cloud and edge computing protocols make it possible to offer computationally heavy applications to mobile devices via computational offloading from devices to nearby edge servers or more powerful, but remote, cloud servers.

Edge-computing

The Broadcast Approach in Communication Networks

no code implementations18 Jan 2021 Ali Tajer, Avi Steiner, Shlomo Shamai

However, when the variations are infrequent, their temporal average can deviate significantly from the channel's ergodic mode, rendering a lack of instantaneous performance guarantees.

Information Theory Information Theory

Coordinated Multi Point Transmission and Reception for Mixed-Delay Traffic

no code implementations14 Dec 2020 Homa Nikbkaht, Michele Wigger, Shlomo Shamai

In the model without sectorization, a penalty in sum-MG is incurred whenever one insists on a positive delay-sensitive MG.

Information Theory Information Theory

Broadcast Approach for the Information Bottleneck Channel

no code implementations29 Apr 2020 Avi Steiner, Shlomo Shamai

This work considers a layered coding approach for efficient transmission of data over a wireless block fading channel without transmitter channel state information (CSI), which is connected to a limited capacity reliable link, known as the bottleneck channel.

Information Theory Information Theory

Optimizing Over-the-Air Computation in IRS-Aided C-RAN Systems

no code implementations20 Apr 2020 Daesung Yu, Seok-Hwan Park, Osvaldo Simeone, Shlomo Shamai

Over-the-air computation (AirComp) is an efficient solution to enable federated learning on wireless channels.

Signal Processing Information Theory Information Theory

On the Information Bottleneck Problems: Models, Connections, Applications and Information Theoretic Views

no code implementations31 Jan 2020 Abdellatif Zaidi, Inaki Estella Aguerri, Shlomo Shamai

This tutorial paper focuses on the variants of the bottleneck problem taking an information theoretic perspective and discusses practical methods to solve it, as well as its connection to coding and learning aspects.

Representation Learning Variational Inference

The Capacity Achieving Distribution for the Amplitude Constrained Additive Gaussian Channel: An Upper Bound on the Number of Mass Points

no code implementations10 Jan 2019 Alex Dytso, Semih Yagli, H. Vincent Poor, Shlomo Shamai

Finally, the third part provides bounds on the number of points for the case of $n=1$ with an additional power constraint.

Information Theory Information Theory

On the Capacity of the Peak Power Constrained Vector Gaussian Channel: An Estimation Theoretic Perspective

1 code implementation23 Apr 2018 Alex Dytso, H. Vincent Poor, Shlomo Shamai

This paper characterizes the necessary and sufficient conditions on the constraint $R$ such that the input distribution supported on a single sphere is optimal.

Information Theory Information Theory

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