Résultats de la recherche - (coding OR decoding) (algorithmics OR (algorithm OR (algorithm OR Algorithmssssics)))

Strong Copyright Protection for Language Models via Adaptive Model Fusion par Abad, Javier, Donhauser, Konstantin, Pinto, Francesco, Yang, Fanny

Table des matières: “…-Protecting Fusion (CP-Fuse), an algorithm that adaptively combines language models to minimize…”
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Graph grammars and Physics Informed Neural Networks for simulating of pollution propagation on Spitzbergen par Sikora, Maciej, Oliver-Serra, Albert, Siwik, Leszek, Leszczyńska, Natalia, Ciesielski, Tomasz Maciej, Valseth, Eirik, Leszczyński, Jacek, Paszyńska, Anna, Paszyński, Maciej

Table des matières: “…-edge refinement algorithm. This solver is used for an exemplary application: performing three…”
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Applicability criteria of proper charge neutrality and special relativistic MHD models extended by two-fluid effects par Yoshino, Shuntaro, Hirota, Makoto, Hattori, Yuji

Table des matières: “… algorithm, which is the most time-consuming part of the RMHD code, is no longer required to compute…”
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Advanced Persistent Threats (APT) Attribution Using Deep Reinforcement Learning par Basnet, Animesh Singh, Ghanem, Mohamed Chahine, Dunsin, Dipo, Sowinski-Mydlarz, Wiktor

Table des matières: “… coding, and numerous adjustments based on the insights gathered from predecessor models and contemporary…”
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Stochastic inflation and non-perturbative power spectrum beyond slow roll par Sharma, Devanshu

Table des matières: “… the large-scale behaviour of primordial fluctuations. In this work, we develop a numerical code to capture…”
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Hamiltonian Monte Carlo-Based Near-Optimal MIMO Signal Detection par Hagiwara, Junichiro, Nishimura, Toshihiko, Sato, Takanori, Ogawa, Yasutaka, Ohgane, Takeo

Table des matières: “… into a continuous problem while leveraging the efficient Hamiltonian Monte Carlo algorithm…”
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Can large language models be privacy preserving and fair medical coders? par Dadsetan, Ali, Soleymani, Dorsa, Zeng, Xijie, Rudzicz, Frank

Table des matières: “…Protecting patient data privacy is a critical concern when deploying machine learning algorithms…”
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Edicho: Consistent Image Editing in the Wild par Bai, Qingyan, Ouyang, Hao, Xu, Yinghao, Wang, Qiuyu, Yang, Ceyuan, Cheng, Ka Leong, Shen, Yujun, Chen, Qifeng

Table des matières: “… algorithm enjoys a plug-and-play nature and is compatible to most diffusion-based editing methods…”
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TeNeS-v2: Enhancement for Real-Time and Finite Temperature Simulations of Quantum Many-Body Systems par Motoyama, Yuichi, Okubo, Tsuyoshi, Yoshimi, Kazuyoshi, Morita, Satoshi, Aoyama, Tatsumi, Kato, Takeo, Kawashima, Naoki

Table des matières: “…, the technical complexity of TPS/PEPS-based coding is often too much for researchers to handle. To reduce…”
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Formally Verifying a Transformation from MLTL Formulas to Regular Expressions par Wang, Zili, Kosaian, Katherine, Rozier, Kristin Yvonne

Table des matières: “… itself works correctly. To that end, we verify the WEST algorithm, which converts MLTL formulas…”
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Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks par Kim, Jeongmo, Park, Yisak, Kim, Minung, Han, Seungyul

Table des matières: “… Training (TAVT), a novel algorithm that accurately captures task characteristics for both training and OOD…”
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Performance Review on LLM for solving leetcode problems par Wang, Lun, Shi, Chuanqi, Du, Shaoshui, Tao, Yiyi, Shen, Yixian, Zheng, Hang, Shen, Yanxin, Qiu, Xinyu

Table des matières: “…) in solving programming challenges from Leetcode, a widely used platform for algorithm practice and technical…”
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Sparse Dictionary Learning for Image Recovery by Iterative Shrinkage par Shabani, Shima, Khoshghiaferezaee, Mohammadsadegh, Breuß, Michael

Table des matières: “…In this paper we study the sparse coding problem in the context of sparse dictionary learning…”
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Generative Modeling for Mathematical Discovery par Ellenberg, Jordan S., Fraser-Taliente, Cristofero S., Harvey, Thomas R., Srivastava, Karan, Sutherland, Andrew V.

Table des matières: “…We present a new implementation of the LLM-driven genetic algorithm {\it funsearch}, whose aim…”
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ScalerEval: Automated and Consistent Evaluation Testbed for Auto-scalers in Microservices par Xie, Shuaiyu, Wang, Jian, Luo, Yang, Yong, Yunqing, Tan, Yuzhen, Li, Bing

Table des matières: “… to accommodate fluctuating workloads. Despite the introduction of many sophisticated auto-scaling algorithms…”
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DeepCS-TRD, a Deep Learning-based Cross-Section Tree Ring Detector par Marichal, Henry, Casaravilla, Verónica, Power, Candice, Mello, Karolain, Mazarino, Joaquín, Lucas, Christine, Profumo, Ludmila, Passarella, Diego, Randall, Gregory

Table des matières: “…Here, we propose Deep CS-TRD, a new automatic algorithm for detecting tree rings in whole cross…”
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Kinship Verification through a Forest Neural Network par Nazari, Ali, Moghaddam, Mohsen Ebrahimi, Borzoei, Omidreza

Table des matières: “… representation algorithms. Moreover, we designed the structure of the classification module and introduced a new…”
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ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA par Shi, Zhengyuan, Li, Zeju, Ma, Chengyu, Zhou, Yunhao, Zheng, Ziyang, Liu, Jiawei, Pan, Hongyang, Zhou, Lingfeng, Li, Kezhi, Zhu, Jiaying, Yan, Lingwei, He, Zhiqiang, Xue, Chenhao, Jiang, Wentao, Yang, Fan, Sun, Guangyu, Yang, Xiaoyan, Chen, Gang, Shi, Chuan, Chu, Zhufei, Yang, Jun, Xu, Qiang

Table des matières: “…. ForgeEDA includes diverse circuit representations such as Register Transfer Level (RTL) code, Post-mapping…”
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Merging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation par Almuzairee, Abdulaziz, Patil, Rohan, Bhatt, Dwait, Christensen, Henrik I.

Table des matières: “… And Disentanglement (MAD) algorithm that efficiently merges views to increase sample efficiency while simultaneously…”
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Layer-wise Quantization for Quantized Optimistic Dual Averaging par Nguyen, Anh Duc, Markov, Ilia, Wu, Frank Zhengqing, Ramezani-Kebrya, Ali, Antonakopoulos, Kimon, Alistarh, Dan, Cevher, Volkan

Table des matières: “… quantization framework with tight variance and code-length bounds, adapting to the heterogeneities over…”
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