Copertina

Distributed and Rate-Adaptive Feature Compression

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Deshmukh, Aditya, Veeravalli, Venugopal V., Verma, Gunjan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Theory Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Finite-Horizon Quickest Change Detection Balancing Latency with False Alarm Probability
di: Huang, Yu-Han, et al.
Pubblicazione: (2025)

Is Prior-Free Black-Box Non-Stationary Reinforcement Learning Feasible?
di: Gerogiannis, Argyrios, et al.
Pubblicazione: (2024)

Principled Detection of Hallucinations in Large Language Models via Multiple Testing
di: Li, Jiawei, et al.
Pubblicazione: (2025)

Compressing Chemistry Reveals Functional Groups
di: Sharma, Ruben, et al.
Pubblicazione: (2025)

High-Rate Quantized Matrix Multiplication II
di: Ordentlich, Or, et al.
Pubblicazione: (2026)

LASER: Linear Compression in Wireless Distributed Optimization
di: Makkuva, Ashok Vardhan, et al.
Pubblicazione: (2023)

AlphaZip: Neural Network-Enhanced Lossless Text Compression
di: Narashiman, Swathi Shree, et al.
Pubblicazione: (2024)

Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization
di: Borzechowski, Florian, et al.
Pubblicazione: (2025)

Interpretability as Compression: Reconsidering SAE Explanations of Neural Activations with MDL-SAEs
di: Ayonrinde, Kola, et al.
Pubblicazione: (2024)

A General Error-Theoretical Analysis Framework for Constructing Compression Strategies
di: Zhang, Boyang, et al.
Pubblicazione: (2025)

Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
di: Kudo, Sota, et al.
Pubblicazione: (2024)

FibQuant: Universal Vector Quantization for Random-Access KV-Cache Compression
di: Lee, Namyoon, et al.
Pubblicazione: (2026)

GeoIB: Geometry-Aware Information Bottleneck via Statistical-Manifold Compression
di: Wang, Weiqi, et al.
Pubblicazione: (2026)

Haiku to Opus in Just 10 bits: LLMs Unlock Massive Compression Gains
di: Rinberg, Roy, et al.
Pubblicazione: (2026)

Localized Adaptive Risk Control
di: Zecchin, Matteo, et al.
Pubblicazione: (2024)

Causally-Guided Diffusion for Stable Feature Selection
di: Malarkkan, Arun Vignesh, et al.
Pubblicazione: (2026)

Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
di: Heurtel-Depeiges, David, et al.
Pubblicazione: (2024)

Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
di: Pan, Zhixuan, et al.
Pubblicazione: (2025)

PrismQuant: Rate-Distortion-Optimal Vector Quantization for Gaussian-Mixture Sources
di: Park, Bumsu, et al.
Pubblicazione: (2026)

Semantic Rate Distortion and Posterior Design: Compute Constraints, Multimodality, and Strategic Inference
di: Akyol, Emrah
Pubblicazione: (2026)

Partial Information Decomposition for Data Interpretability and Feature Selection
di: Westphal, Charles, et al.
Pubblicazione: (2024)

Deep Randomized Distributed Function Computation (DeepRDFC): Neural Distributed Channel Simulation
di: Bergström, Didrik, et al.
Pubblicazione: (2026)

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning
di: Samuelson, Jeremy J
Pubblicazione: (2026)

Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation
di: Falahati, Ali, et al.
Pubblicazione: (2024)

Polynomial Context-Truncation Sensitivity in Autoregressive Language Models: Sequential Wyner-Ziv Bounds for KV Cache Compression
di: Kim, Munsik
Pubblicazione: (2026)

Entropy-informed Decoding: Adaptive Information-Driven Branching
di: Evans, Benjamin Patrick, et al.
Pubblicazione: (2026)

Quickest Change Detection with Confusing Change
di: Chen, Yu-Zhen Janice, et al.
Pubblicazione: (2024)

Adaptive $k$-nearest neighbor classifier based on the local estimation of the shape operator
di: Levada, Alexandre Luís Magalhães, et al.
Pubblicazione: (2024)

Generative Decompression: Optimal Lossy Decoding Against Distribution Mismatch
di: Khosravirad, Saeed R., et al.
Pubblicazione: (2026)

Language Modeling Is Compression
di: Delétang, Grégoire, et al.
Pubblicazione: (2023)

WDMoE: Wireless Distributed Large Language Models with Mixture of Experts
di: Xue, Nan, et al.
Pubblicazione: (2024)

Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
di: Yu, Wenrui, et al.
Pubblicazione: (2024)

MambaJSCC: Adaptive Deep Joint Source-Channel Coding with Generalized State Space Model
di: Wu, Tong, et al.
Pubblicazione: (2024)

Fast Rates for Offline Contextual Bandits with Forward-KL Regularization under Single-Policy Concentrability
di: Zhao, Qingyue, et al.
Pubblicazione: (2026)

Compression Represents Intelligence Linearly
di: Huang, Yuzhen, et al.
Pubblicazione: (2024)

Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
di: Amaefuna, Theophilus, et al.
Pubblicazione: (2026)

Memorization-Compression Cycles Improve Generalization
di: Yu, Fangyuan
Pubblicazione: (2025)

Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach
di: Huang, Yu-Han, et al.
Pubblicazione: (2025)

Learning is Forgetting: LLM Training As Lossy Compression
di: Conklin, Henry C., et al.
Pubblicazione: (2026)

Towards Efficient VLMs: Information-Theoretic Driven Compression via Adaptive Structural Pruning
di: Xu, Zhaoqi, et al.
Pubblicazione: (2025)