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.
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Low-Weight Canonical Logical Bases from Pair-Partition Codes
We construct complete canonical logical bases for qubit CSS codes by assigning quaternary coefficients to binary circulant permutation matrix pair-partition (CPM-PP) checks, constructing and…Learning sparse quantum states from single-qubit measurements
We study the problem of learning a sparse quantum state, an $n$-qubit quantum state whose density matrix has at most $s$ nonzero matrix entries in an unknown product basis.The Hidden Perception Constraint in Task-Aware Compression
With the recent advancements of neural compressors, explicitly incorporating perception constraints into the design of compression schemes has gained significant attention.Bregman Consensus
Consider a community of agents who are seeking consensus on a set of parameters.TORQUE: Optimizing What (not) to Quantize Before and After Rotation
Uniform random rotations are an effective preprocessing step for quantization: they make normalized coordinate distributions approximately Gaussian, enabling the use of codebooks optimized offline.From Classical to Quantum Channels: Achieving Positive Covert Rates
In this paper, we study the conditions under which covert communication at positive rates is feasible over discrete memoryless classical, classical-quantum, and quantum channels.The Statistical Benefits of Multiple Responses for Learning from Demonstrations
Many generative systems return multiple candidate responses and are evaluated according to the best one.StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networks
In Integrated Sensing and Communications (ISAC), radar sensing must operate under chirp subsampling with up to 90\% missing data.The cost of useful natural gradient updates
What information is needed to turn a natural-gradient direction into a useful finite update?Short-Length Code Designs for Integrated Sensing and Communications: A Deep Learning Approach
Integrated sensing and communication (ISAC) enables joint communication and sensing using a shared waveform, but its signal design is challenging due to the inherent trade-off between the two…Geometric Inductive Biases for Semi-Supervised Equalization: The Constellation-Aware Transformer
Decoding signals over unknown channels with minimal pilot overhead is a critical challenge in next-generation communications.Non-Adaptive Learning of Sparse Erdős--Rényi Graphs via Affine Splitting
Graph learning from edge-detecting queries concerns the reconstruction of an unknown edge set on a known vertex set.Concurrent Coded Signal-Multiplexing Ranging for Half-Duplex Asynchronous Networks
Signal-multiplexing network ranging (SM-NR) shares broadcasts across node pairs, but its sequential operation leads to a ranging cycle that grows linearly with network size.SymNetPro: LOS-Aware Directional Multi-Transmitter Localization from Sparse Radio Observations
Directional multi-transmitter localization from sparse received-power observations is difficult because the receiver observes only the source-unresolved aggregate field: multiple directional sources…An exponential strong converse for private communication over degradable quantum channels
We prove an exponential strong converse for the unassisted private capacity of every finite-dimensional degradable quantum channel.One-Step Generative Modeling via Unbalanced Optimal Transport
Drifting models enable one-step generation by amortizing distribution transport into training, but this efficiency places greater demands on the transport field estimated at each update.Domain Adaptation with Target Information via Doubly-Anchored Distributionally Robust Optimization
Domain Adaptation (DA) often lacks worst-case guarantees, while Distributionally Robust Optimization (DRO) based only on source data centers its ambiguity set at the source law and ignores available…Threat-Aware Energy-Efficient Deployment for Dynamic UAV Networks: A Multi-Agent RL Approach
Ensuring operational safety in threat-prone environments remains a critical challenge for multi-UAV networks serving as aerial base stations.Moment Ambiguity and the Limits of Robust Stochastic Optimization
We study fundamental information-theoretic limits of robust stochastic optimization when the distribution is known only through its exact moment sequence.Bayesian Optimization with Fisher Information Geometry: Gradient Bounds and Trust-Region Methods
We study Bayesian optimization (BO) through the lens of information geometry.