Risultati della ricerca - decoding (Algorithmssics OR algorithm)

Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving di Zhao, Zihan, Lu, Baotong, Lin, Shengjie, Chen, Yizou, Liu, Jing, Zhang, Yanqi, Miao, Ziming, Yang, Ming-Chang, Shen, Haiying, Chen, Qi, Yang, Fan

Sommario: “... per decoding step and extending the KV storage to CPU memory. In practice, however, these algorithmic...”
Testo

Adaptive Entropy Lightweight Encryption Estimate for Software Defined Network to Mitigate Data Security Threats in Smart Cities di Sunil Kumar Shah, Raghavendra Sharma, Neeraj Shukla

Sommario: “..., with lightweight algorithms posing limitations due to their lack of high avalanche effects. Thus, a novel Adaptive...”
Testo

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training di Feng, Xidong, Wan, Ziyu, Wen, Muning, McAleer, Stephen Marcus, Wen, Ying, Zhang, Weinan, Wang, Jun

Sommario: “... the reasoning capabilities of LLMs by using tree-search algorithms to guide multi-step reasoning. These methods...”
Testo

Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses di Abdelaleem, Eslam, Nemenman, Ilya, Martini, K. Michael

Sommario: “... that in a decoder graph (defining a generative model for data). Using this approach, we rederive existing...”
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Bayesian Recursive Information Optical Imaging: A Ghost Imaging Scheme Based on Bayesian Filtering di Du, Long-Kun, Hu, Chenyu, Liu, Shuang, Deng, Chenjin, Wang, Chaoran, Bo, Zunwang, Chen, Mingliang, Liu, Wei-Tao, Han, Shensheng

Sommario: “... in an encoded form and subsequently decoded via processing algorithms, which is quite in line...”
Testo

Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth di Kögler, Kevin, Shevchenko, Alexander, Hassani, Hamed, Mondelli, Marco

Sommario: “.... Namely, the performance of the algorithm is the same as if it was compressing a Gaussian source...”
Testo

Trainable Joint Channel Estimation, Detection and Decoding for MIMO URLLC Systems di Sun, Yi, Shen, Hong, Li, Bingqing, Xu, Wei, Zhu, Pengcheng, Hu, Nan, Zhao, Chunming

Sommario: “..., and decoding (JCDD) for MIMO URLLC systems encoded by short low-density parity-check (LDPC) codes. Specifically...”
Testo

Cross-Scan Mamba with Masked Training for Robust Spectral Imaging di Tian, Wenzhe, Zeng, Haijin, Zhao, Yin-Ping, Chen, Yongyong, Wang, Zhen, Li, Xuelong

Sommario: “...Snapshot Compressive Imaging (SCI) enables fast spectral imaging but requires effective decoding...”
Testo

First Order Stochastic Optimization with Oblivious Noise di Diakonikolas, Ilias, Karmalkar, Sushrut, Park, Jongho, Tzamos, Christos

Sommario: “... of inliers $α$ is less than $1/2$. Our main result is an efficient list-decodable learner that recovers a...”
Testo

Online Optimization for Learning to Communicate over Time-Correlated Channels di Wu, Zheshun, Li, Junfan, Xu, Zenglin, Sun, Sumei, Liu, Jie

Sommario: “... on two specific tasks: optimizing channel decoders for time-correlated fading channels and selecting...”
Testo

Beyond GFVC: A Progressive Face Video Compression Framework with Adaptive Visual Tokens di Chen, Bolin, Yin, Shanzhi, Zhang, Zihan, Chen, Jie, Liao, Ru-Ling, Zhu, Lingyu, Wang, Shiqi, Ye, Yan

Sommario: “... communication. However, these GFVC algorithms are sometimes faced with unstable reconstruction quality...”
Testo

Enhancing LMMSE Performance with Modest Complexity Increase via Neural Network Equalizers di Rozenfeld, Vadim, Raphaeli, Dan, Bialer, Oded

Sommario: “...The BCJR algorithm is renowned for its optimal equalization, minimizing bit error rate (BER) over...”
Testo

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention di Yuan, Jingyang, Gao, Huazuo, Dai, Damai, Luo, Junyu, Zhao, Liang, Zhang, Zhengyan, Xie, Zhenda, Wei, Y. X., Wang, Lean, Xiao, Zhiping, Wang, Yuqing, Ruan, Chong, Zhang, Ming, Liang, Wenfeng, Zeng, Wangding

Sommario: “... NSA, a Natively trainable Sparse Attention mechanism that integrates algorithmic innovations...”
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SPEX: Scaling Feature Interaction Explanations for LLMs di Kang, Justin Singh, Butler, Landon, Agarwal, Abhineet, Erginbas, Yigit Efe, Pedarsani, Ramtin, Ramchandran, Kannan, Yu, Bin

Sommario: “... channel decoding algorithm to efficiently identify important interactions. We perform experiments across...”
Testo

SparseMamba-PCL: Scribble-Supervised Medical Image Segmentation via SAM-Guided Progressive Collaborative Learning di Qiu, Luyi, Till, Tristan, Guo, Xiaobao, Kong, Adams Wai-Kin

Sommario: “... Learning framework that leverages novel algorithms and the Med-SAM foundation model to enhance information...”
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ARMOR: Empowering Multimodal Understanding Model with Interleaved Multimodal Generation Capability di Sun, Jianwen, Feng, Yukang, Li, Chuanhao, Zhang, Fanrui, Li, Zizhen, Ai, Jiaxin, Zhou, Sizhuo, Dai, Yu, Zhang, Shenglin, Zhang, Kaipeng

Sommario: “... encoder-decoder architecture with a forward-switching mechanism is introduced to unify embedding space...”
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SWIPT in Cell-Free Massive MIMO Using Stacked Intelligent Metasurfaces di Hua, Thien Duc, Mohammadi, Mohammadali, Ngo, Hien Quoc, Matthaiou, Michail

Sommario: “...-decoding receivers (IRs) and the average sum of harvested energy (sum-HE) at the energy-harvesting...”
Testo

StainPIDR: A Pathological Image Decouplingand Reconstruction Method for Stain Normalization Based on Color Vector Quantization and Structure Restaining di Chen, Zheng

Sommario: “... color features, and decoding the stained structure features to normalized pathological images. We assume...”
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GRACE: Designing Generative Face Video Codec via Agile Hardware-Centric Workflow di Wan, Rui, Zheng, Qi, Zhang, Ruoyu, Chen, Bu, Liu, Jiaming, Li, Min, Jing, Minge, Zhou, Jinjia, Fan, Yibo

Sommario: “... compression. However, deploying its intricate decoder on resource and power-constrained edge devices presents...”
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Differentiable Filtering for Learning Hidden Markov Models di Chen, Reginald Zhiyan, Chang, Heng-Sheng, Mehta, Prashant G.

Sommario: “... their parameters from observations remains challenging. Classical methods like the Baum-Welch algorithm...”
Testo