Risultati della ricerca - coding (algorithmics OR (algorithm OR (Algorithmssssics OR (algorithm OR algorithm))))

Proxy Discrimination After Students for Fair Admissions di Fagan, Frank

Sommario: “... accuracy rates, but one uses zip code and the other does not, then the second algorithm can be said to have...”
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Efficiently Vectorized MCMC on Modern Accelerators di Dance, Hugh, Glaser, Pierre, Orbanz, Peter, Adams, Ryan

Sommario: “... MCMC algorithms is often now as simple as invoking those tools on single-chain code. Whilst convenient...”
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RankEvolve: Automating the Discovery of Retrieval Algorithms via LLM-Driven Evolution di Nian, Jinming, Li, Fangchen, Park, Dae Hoon, Fang, Yi

Sommario: “... based on AlphaEvolve, in which candidate ranking algorithms are represented as executable code...”
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Partitioning Unstructured Sparse Tensor Algebra for Load-Balanced Parallel Execution di Chougule, Atharva, Root, Alexander J, Lacouture, Rubens, Yan, Bobby, Yadav, Rohan, Kjolstad, Fredrik

Sommario: “... algorithm that provably load balances the computation of any sparse tensor algebra expression across...”
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Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates di Roulet, Vincent, Srinivasa, Siddhartha, Fazel, Maryam, Harchaoui, Zaid

Sommario: “...Iterative optimization algorithms depend on access to information about the objective function...”
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RLLTE: Long-Term Evolution Project of Reinforcement Learning di Yuan, Mingqi, Zhang, Zequn, Xu, Yang, Luo, Shihao, Li, Bo, Jin, Xin, Zeng, Wenjun

Sommario: “... for reinforcement learning (RL) research and application. Beyond delivering top-notch algorithm implementations...”
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Walking Your Frog Fast in 4 LoC di Meinert, Nis

Sommario: “... quadratic runtime overhead. However, this algorithm relies on recursions and is not well suited for modern...”
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Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning di Ye, Kai, Zhou, Hongyi, Zhu, Jin, Quinzan, Francesco, Shi, Chengchun

Sommario: “... existing RLHF algorithms use the Bradley-Terry model, which relies on assumptions about human preferences...”
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Efficient Layered New Bit-Flipping QC-MDPC Decoder for BIKE Post-Quantum Cryptography di Cai, Jiaxuan, Zhang, Xinmiao

Sommario: “...The medium-density parity-check (MDPC) code-based Bit Flipping Key Encapsulation (BIKE) mechanism...”
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Linear Complexity Computation of Code Distance and Minimum Size of Trapping Sets for LDPC Codes with Bounded Treewidth di Peng, Qingqing, Liu, Ke, Yan, Guiying, Wang, Guanghui

Sommario: “...\) in a binary linear code is NP-hard. In this paper, we demonstrate that this problem can be solved...”
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Efficient Algorithms for Constructing Minimum-Weight Codewords in Some Extended Binary BCH Codes di Berman, Amit, Shany, Yaron, Tamo, Itzhak

Sommario: “...We present $O(m^3)$ algorithms for specifying the support of minimum-weight words of extended...”
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The Challenges for Pharmacoepidemiologists Identifying Migraine in Electronic Healthcare Data Sources: A Systematic Literature Review di Joan Forns, Alicia Abellan, Nuria Riera‐Guàrdia, Andrea V. Margulis, Elena Rivero‐Ferrer

Sommario: “... depend on algorithm characteristics and target population. Methods To describe migraine‐identifying...”
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BEAM: Bi-level Memory-adaptive Algorithmic Evolution for LLM-Powered Heuristic Design di Xiang, Chuyang, Wei, Yichen, Ma, Jiale, Wang, Handing, Yan, Junchi

Sommario: “... complex code through iterative local modifications, they still lack a high-level algorithmic modeling...”
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Algorithmic Universality, Low-Degree Polynomials, and Max-Cut in Sparse Random Graphs di Cheairi, Houssam El, Gamarnik, David

Sommario: “... on sparse graphs, provided that an algorithm can be coded as a low-degree polynomial (LDP). We illustrate...”
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IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing di Xie, Guoyang, Wang, Jinbao, Liu, Jiaqi, Lyu, Jiayi, Liu, Yong, Wang, Chengjie, Zheng, Feng, Jin, Yaochu

Sommario: “... manufacturing (IM). Recently, many advanced algorithms have been reported, but their performance deviates...”
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Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal Reasoning di Ghosal, Deepanway, Han, Vernon Toh Yan, Ken, Chia Yew, Poria, Soujanya

Sommario: “... the capabilities of multimodal language models in solving algorithmic puzzles that necessitate both visual...”
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Engineering A Workload-balanced Push-Relabel Algorithm for Massive Graphs on GPUs di Hsieh, Chou-Ying, Lin, Po-Chieh, Kuo, Sy-Yen

Sommario: “...The push-relabel algorithm is an efficient algorithm that solves the maximum flow/ minimum cut...”
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Can Large Language Models Invent Algorithms to Improve Themselves?: Algorithm Discovery for Recursive Self-Improvement through Reinforcement Learning di Ishibashi, Yoichi, Yano, Taro, Oyamada, Masafumi

Sommario: “... employs an iterative cycle where a seed model generates algorithmic candidates as executable code...”
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LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness di Ye, Tong, Huang, Weigang, Zhang, Xuhong, Ma, Tengfei, Liu, Peiyu, Yin, Jianwei, Wang, Wenhai

Sommario: “... in code generation. Current research primarily focuses on the correctness of generated code, while...”
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Large Language Model-Powered Evolutionary Code Optimization on a Phylogenetic Tree di Zhao, Leyi, Huang, Weijie, Guo, Yitong, Bian, Jiang, Wang, Chenghong, Zhang, Xuhong

Sommario: “...Optimizing scientific computing algorithms for modern GPUs is a labor-intensive and iterative...”
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