Theory & Algorithms · Computer Science & AI
Information Theory
The newest papers in Information Theory that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
474 papers, from 4 September 2026 to 5 November 2026: 474 arXiv preprints.
Get the few papers worth your time in Information Theory every morning.
Follow Information Theory and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 8
POST-MIMO: Partition-Oriented Semantic Transmission for MIMO Point Cloud Delivery
Point clouds have become a fundamental data format for emerging three dimensional (3D) applications, while their wireless delivery remains challenging due to the large data volume and irregular…Estimation of Quantum Umlaut Information
Quantifying correlations is important for understanding how quantum states and channels support information processing.Scaled-Gradient Hard Thresholding Algorithms for Sparse Signal Recovery
Thresholding methods provide a simple iterative framework for sparse signal recovery by combining a search direction with a thresholding operation.Sparse descent subspace-Newton thresholding algorithm for sparse optimization problems
In this paper, we propose a sparse descent direction derived from the Newton direction within a low-dimensional subspace for sparse optimization problems.Beamfocusing Beyond the Near Field: Frequency Diverse Arrays for OFDM-ISAC Systems
Traditional phased arrays (PAs) achieve near-field (NF) beamfocusing through spherical wavefront curvature, but lose this range selectivity in the far field (FF).LEO Constellation Analysis for Satellite IoT: An Analysis of Coverage Gaps and Retransmissions
Low Earth Orbit (LEO) constellations are a promising way to connect Internet of Things (IoT) devices beyond terrestrial coverage, yet the intermittent visibility of their satellites imposes hard…On $t$-designs supported by self-orthogonal codes
We study self-orthogonal $t$-$(v,k,λ)$ designs satisfying the condition that the codes generated by the designs are self-orthogonal codes whose codewords of minimum weight $k$ correspond to the…Secure Deterministic Identification with Feedback and Sensing over State-Dependent Wiretap Channels
Identification differs from classical transmission in that the receiver determines whether a particular identity was sent rather than recovering a message.Shaping and Finite-Blocklength Analysis of Quaternionic Alamouti-Type Codes
We study finite $2\times2$ Alamouti-type space--time codes associated with classical maximal orders in definite quaternion algebras over $\mathbb Q$.Feasibility of Common-Stream-Only Sensing in ZF-RSMA with Imperfect CSIT
Reusing the Rate-Splitting Multiple Access (RSMA) common stream for sensing eliminates dedicated probing signals in Integrated Sensing and Communication (ISAC), but creates a feasibility bottleneck…Characterizations and MacWilliams-Like Identities of Weakly Regular Bent Partitions
Bent partitions play a significant role in the theory of bent functions.Channel dichotomies
We study channel interconversion under non-signalling superchannels, where the asymptotic conversion rate is given by the ratio of the channel capacities.Batch Universal Prediction via Conditional Additive Smoothing
Modern language models motivate renewed interest in universal prediction problems in which a predictor can exploit previously observed data before predicting a fresh sequence.Rates and Nearly-Lossless State over a Multi-Access Channel with Causal State Information
The problem of transmitting both data and state over a memoryless state-dependent multi-access channel with causal state information is addressed.On approximate support versions of Donoho--Stark uncertainty principles for $k$-Hadamard operators
In this paper we present results related to Donoho--Stark type uncertainty principles that were proved in the article "The uncertainty principle: variations on a theme" by Wigderson and Wigderson…Statistical Foundations of Reinforcement Learning: A Non-Asymptotic Perspective
Reinforcement learning (RL) embodies a foundational paradigm for sequential decision-making in the face of uncertainty.Extremal character spectra of finite projective systems
Let $\mathcal M$ be a finite spanning multiset of points in ${\rm PG}(k-1,q)$, and let ${\rm Char}_{\mathcal M}$ be its character function.Capacity Meets the Four Subspace Problem: Distributed Linear Computation and the Cross-Ratio
$K$ users each observe a fixed linear function of common data over a finite field of characteristic $p$, and a server must recover another fixed linear function with zero error from one message sent…Embodied Movable Antennas
This paper introduces embodied movable antennas (MAs), a new MA architecture that rethinks the source of antenna mobility.The Pareto Secretary Problem
The Pareto secretary problem asks for online selection of a Pareto-maximal observation from an i.i.d. sample: no other observation is at least as good in every coordinate and strictly better in one.