Risultati della ricerca - (coding OR (endedededededededededededededededededededededededededecoding OR Decoding)) algorithm

Enhancing PPO with Trajectory-Aware Hybrid Policies di Liu, Qisai, Jiang, Zhanhong, Yang, Hsin-Jung, Khosravi, Mahsa, Waite, Joshua R., Sarkar, Soumik

Sommario: “...Proximal policy optimization (PPO) is one of the most popular state-of-the-art on-policy algorithms...”
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A New Execution Model and Executor for Adaptively Optimizing the Performance of Parallel Algorithms Using HPX Runtime System di Mohammadiporshokooh, Karame, Brandt, Steven R., Kaiser, Hartmut

Sommario: “...Developing parallel algorithms efficiently requires careful management of concurrency across...”
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Efficient Computation of Marton's Error Exponent via Constraint Decoupling di Ye, Jiachuan, Wu, Shitong, Chen, Lingyi, Zhang, Wenyi, Wu, Huihui, Wu, Hao

Sommario: “...The error exponent in lossy source coding characterizes the asymptotic decay rate of error...”
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Fast and Optimal Incremental Parametric Procedure for the Densest Subgraph Problem: An Experimental Study di Hochbaum, Dorit S., Irribarra-Cortés, Ayleen, Goldschmidt, Olivier, Asín-Achá, Roberto

Sommario: “... algorithms face computational and scalability limitations, leading to the adoption of faster, but non-optimal...”
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CUROCKET: Optimizing ROCKET for GPU di Stüven, Ole, Moenck, Keno, Schüppstuhl, Thorsten

Sommario: “...ROCKET (RandOm Convolutional KErnel Transform) is a feature extraction algorithm created for Time...”
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Reinforced Generation of Combinatorial Structures: Ramsey Numbers di Nagda, Ansh, Raghavan, Prabhakar, Thakurta, Abhradeep

Sommario: “...$, and $\mathbf{R}(4, 20)$ from $234$ to $237$. These results were achieved using AlphaEvolve, an LLM-based code...”
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Provably Guaranteed Polytopic Uncertainty Quantification for SLAM di Zeng, Guangyang, Gao, Yulong, Shen, Yuan, Chen, Lingpeng, Li, Haoying, Shi, Guodong, Wu, Junfeng

Sommario: “... presents provably guaranteed UQ algorithms for 3D-3D landmark-based SLAM. The algorithms consist of three...”
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Incentive-Aware Recommender Systems in Two-Sided Markets di Dai, Xiaowu, Xu, Wenlu, Qi, Yuan, Jordan, Michael I.

Sommario: “... algorithms satisfy an ex-post fairness criterion, which protects agents from over-exploitation. All code...”
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FRENETIX: A High-Performance and Modular Motion Planning Framework for Autonomous Driving di Trauth, Rainer, Moller, Korbinian, Wuersching, Gerald, Betz, Johannes

Sommario: “... sampling-based trajectory planning algorithm. This approach effectively tackles the challenges of solution...”
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KetGPT - Dataset Augmentation of Quantum Circuits using Transformers di Apak, Boran, Bandic, Medina, Sarkar, Aritra, Feld, Sebastian

Sommario: “...-written algorithm-based code (e.g., order of gates and qubits). Our three-fold verification process...”
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DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime di Luo, Zhiyao, Zhu, Mingcheng, Liu, Fenglin, Li, Jiali, Pan, Yangchen, Zhou, Jiandong, Zhu, Tingting

Sommario: “... algorithms within these contexts. To address this gap, we introduce \textit{DTR-Bench}, a benchmarking...”
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TSI-Bench: Benchmarking Time Series Imputation di Du, Wenjie, Wang, Jun, Qian, Linglong, Yang, Yiyuan, Ibrahim, Zina, Liu, Fanxing, Wang, Zepu, Liu, Haoxin, Zhao, Zhiyuan, Zhou, Yingjie, Wang, Wenjia, Ding, Kaize, Liang, Yuxuan, Prakash, B. Aditya, Wen, Qingsong

Sommario: “... the development of numerous deep learning algorithms for time series imputation, the community lacks standardized...”
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A faster multipole Legendre-Chebyshev transform di Mortensen, Mikael

Sommario: “...This paper describes a fast algorithm for transforming Legendre coefficients into Chebyshev...”
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Parallel Contraction Hierarchies Can Be Efficient and Scalable di Wan, Zijin, Dong, Xiaojun, Wang, Letong, Zhu, Enzuo, Gu, Yan, Sun, Yihan

Sommario: “...Contraction Hierarchies (CH) (Geisberger et al., 2008) is one of the most widely used algorithms...”
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Fast and Near-Optimal Collision-Free Robot Scheduling On Paths di Adamson, Duncan, Flaherty, Nathan, Potapov, Igor, Spirakis, Paul G., Zamaraeva, Elena

Sommario: “... algorithm (PA) introduced in arXiv:2402.12019 and present three baselines for comparison: an integer...”
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Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks di Abbott, Vincent, Kamiya, Kotaro, Glowacki, Gerard, Atsumi, Yu, Zardini, Gioele, Maruyama, Yoshihiro

Sommario: “... automated compilation methods are poor, and efficient algorithms require years of human development...”
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The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models di Xiao, Yang, Li, Gen, Ji, Jie, Ye, Ruimeng, Ma, Xiaolong, Hui, Bo

Sommario: “... and unlearning algorithms. Our code is released at https://github.com/NKUShaw/SparseModels . ...”
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Prompting Lipschitz-constrained network for multiple-in-one sparse-view CT reconstruction di Shi, Baoshun, Jiang, Ke, Lian, Qiusheng, Yu, Xinran, Fu, Huazhu

Sommario: “... analyzing the convergence of the proposed iterative algorithms. The data and code are publicly available...”
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Square-root Time Atom Reconfiguration Plan for Lattice-shaped Mobile Tweezers di Aoyama, Koki, Tomita, Takafumi, Ino, Fumihiko

Sommario: “...This paper proposes a scalable planning algorithm for creating defect-free atom arrays in neutral...”
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Linear-Time Approximation Algorithms for Computing Numerical Summation with Provably Small Errors di Kao, Ming-Yang, Wang, Jie

Sommario: “... approximation algorithm that has a provably small error for arbitrary $X$. Our algorithm incurs a worst-case...”
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