Résultats de la recherche - decoding ((algorithmics OR (algorithm OR algorithm)) OR (algorithm OR Algorithmssics))

Adapting to Covariate Shift in Real-time by Encoding Trees with Motion Equations par Foong, Tham Yik, Zhang, Heng, Yuan, Mao Po, Vargas, Danilo Vasconcellos

Table des matières: “… Xenovert, an adaptive algorithm that can dynamically adapt to changes in input distribution. It is a…”
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Exploring and Improving Drafts in Blockwise Parallel Decoding par Kim, Taehyeon, Suresh, Ananda Theertha, Papineni, Kishore, Riley, Michael, Kumar, Sanjiv, Benton, Adrian

Table des matières: “… hampered by the slow inference speeds inherent in sequential token generation. Blockwise parallel decoding…”
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TK-Planes: Tiered K-Planes with High Dimensional Feature Vectors for Dynamic UAV-based Scenes par Maxey, Christopher, Choi, Jaehoon, Lee, Yonghan, Lee, Hyungtae, Manocha, Dinesh, Kwon, Heesung

Table des matières: “… Field (NeRF), wherein our algorithm stores a set of tiered feature vectors. The tiered feature vectors…”
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Directly Training Temporal Spiking Neural Network with Sparse Surrogate Gradient par Li, Yang, Zhao, Feifei, Zhao, Dongcheng, Zeng, Yi

Table des matières: “… direct training of SNNs for various applications. The surrogate gradient (SG) algorithm has recently…”
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Open-Source Conversational AI with SpeechBrain 1.0 par Ravanelli, Mirco, Parcollet, Titouan, Moumen, Adel, de Langen, Sylvain, Subakan, Cem, Plantinga, Peter, Wang, Yingzhi, Mousavi, Pooneh, Della Libera, Luca, Ploujnikov, Artem, Paissan, Francesco, Borra, Davide, Zaiem, Salah, Zhao, Zeyu, Zhang, Shucong, Karakasidis, Georgios, Yeh, Sung-Lin, Champion, Pierre, Rouhe, Aku, Braun, Rudolf, Mai, Florian, Zuluaga-Gomez, Juan, Mousavi, Seyed Mahed, Nautsch, Andreas, Nguyen, Ha, Liu, Xuechen, Sagar, Sangeet, Duret, Jarod, Mdhaffar, Salima, Laperriere, Gaelle, Rouvier, Mickael, De Mori, Renato, Esteve, Yannick

Table des matières: “… models and the complete "recipes" of code and algorithms required for training them. This paper presents…”
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Menichetti's nonassociative $G$-crossed product algebras and Menichetti codes par Pumpluen, Susanne

Table des matières: “… of algebra they display symmetric and cyclic properties which promise efficient decoding algorithms. Well…”
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Joint Beam Scheduling and Resource Allocation for Flexible RSMA-aided Near-Field Communications par Zhou, Jiasi, Zhou, Cong, Mao, Yijie, Tellambura, Chintha

Table des matières: “… is proposed to efficiently manage interference, which carefully selects a subset of legacy users to decode…”
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Numerical Pruning for Efficient Autoregressive Models par Shen, Xuan, Song, Zhao, Zhou, Yufa, Chen, Bo, Liu, Jing, Zhang, Ruiyi, Rossi, Ryan A., Tan, Hao, Yu, Tong, Chen, Xiang, Zhou, Yufan, Sun, Tong, Zhao, Pu, Wang, Yanzhi, Gu, Jiuxiang

Table des matières: “… on compressing decoder-only transformer-based autoregressive models through structural weight pruning to improve…”
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NeuroIncept Decoder for High-Fidelity Speech Reconstruction from Neural Activity par Khanday, Owais Mujtaba, Pérez-Córdoba, José L., Mir, Mohd Yaqub, Najar, Ashfaq Ahmad, Gonzalez-Lopez, Jose A.

Table des matières: “…This paper introduces a novel algorithm designed for speech synthesis from neural activity…”
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EEG-ReMinD: Enhancing Neurodegenerative EEG Decoding through Self-Supervised State Reconstruction-Primed Riemannian Dynamics par Wang, Zirui, Song, Zhenxi, Guo, Yi, Liu, Yuxin, Xu, Guoyang, Zhang, Min, Zhang, Zhiguo

Table des matières: “…The development of EEG decoding algorithms confronts challenges such as data sparsity, subject…”
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Speculative Decoding and Beyond: An In-Depth Survey of Techniques par Hu, Yunhai, Liu, Zining, Dong, Zhenyuan, Peng, Tianfan, McDanel, Bradley, Zhang, Sai Qian

Table des matières: “… algorithmic innovations and system-level implementations, we examine deployment strategies across computing…”
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On Designing Novel ISI-Reducing Single Error Correcting Codes in an MCvD System par Nath, Tamoghno, Benerjee, Krishna Gopal, Banerjee, Adrish

Table des matières: “… with channel memory and noise. We have also provided encoding and decoding algorithms for the proposed codes…”
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Neural Parametric Mixtures for Path Guiding par Dong, Honghao, Wang, Guoping, Li, Sheng

Table des matières: “… to encode target distributions for path guiding algorithms. We propose to use a continuous and compact…”
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Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations par Sun, Yiyou, Gai, Yu, Chen, Lijie, Ravichander, Abhilasha, Choi, Yejin, Song, Dawn

Table des matières: “… faithful ones. Through theoretical and empirical analyses, we demonstrate that decoder-only transformers…”
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Explicit Lossless Vertex Expanders par Hsieh, Jun-Ting, Lubotzky, Alexander, Mohanty, Sidhanth, Reiner, Assaf, Zhang, Rachel Yun

Table des matières: “… codes of Lin and M. Hsieh with a linear time decoding algorithm. Our construction is based on taking…”
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Hybrid NOMA Assisted Heterogeneous Semantic and Bit Users Communication par Ahmed, Ishtiaque, Musavian, Leila

Table des matières: “… decoding order in slots including heterogeneous users. An optimization problem for the power allocation…”
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Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing par Ma, Ke, Xie, Junfei

Table des matières: “… moving vehicles to nearby RSUs. KATO integrates an attention-inspired encoder-decoder model for selecting…”
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On the Ding and Helleseth's 8th open problem about optimal ternary cyclic codes par He, Dong, Zheng, Peipei, Liao, Qunying

Table des matières: “… storage systems and communication systems due to the efficient encoding and decoding algorithms. In 2013…”
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Tady: A Neural Disassembler without Structural Constraint Violations par Qin, Siliang, Yang, Fengrui, Wang, Hao, Zhang, Bolun, Gao, Zeyu, Zhang, Chao, Chen, Kai

Table des matières: “… and instruction-level decoding that neglect global structural integrity. We introduce Tady, a novel neural…”
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Diffusion Generative Models Meet Compressed Sensing, with Applications to Imaging and Finance par Guo, Zhengyi, Li, Jiatu, Tang, Wenpin, Yao, David D.

Table des matières: “… diffusion model in the latent space; next, apply a compressed sensing algorithm to the samples generated…”
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