Risultati della ricerca - (coding OR decoding) (algorithm OR Algorithmssic)

Probabilistic Hyper-Graphs using Multiple Randomly Masked Autoencoders for Semi-supervised Multi-modal Multi-task Learning di Mihai-Cristian, Pîrvu, Leordeanu, Marius

Sommario: “... the distribution of hyper-edges on each forward pass. Additionally, the model adapts the standard MAE algorithm...”
Testo

FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models di Liu, Junkang, Shang, Fanhua, Liu, Hongying, Tian, Yuxuan, Liu, Yuanyuan, Liu, Jin, Zhu, Kewen, Lin, Zhouchen

Sommario: “... \underline{AdamW} algorithm, called \texttt{FedAdamW}, for training and fine-tuning various large models...”
Testo

CORGI: Efficient Pattern Matching With Quadratic Guarantees di Weitekamp, Daniel

Sommario: “... automatically generate rules from example-driven induction or code synthesis, they can easily produce worst-case...”
Testo

Solving Spatial Supersensing Without Spatial Supersensing di Udandarao, Vishaal, Karthik, Shyamgopal, Nath, Surabhi S., Hochlehnert, Andreas, Bethge, Matthias, Prabhu, Ameya

Sommario: “... object-count predictions unchanged; instead, Cambrian-S inference algorithm relies largely on a shortcut...”
Testo

Spira: Exploiting Voxel Data Structural Properties for Efficient Sparse Convolution in Point Cloud Networks di Adamopoulos, Dionysios, Poulopoulou, Anastasia, Goumas, Georgios, Giannoula, Christina

Sommario: “... for GPUs. Spira proposes (i) a high-performance one-shot search algorithm that builds the kernel map...”
Testo

MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images di Wang, Yaqi, Li, Zhi, Wu, Chengyu, Liu, Jun, Zhang, Yifan, Ni, Jiaxue, Luo, Qian, Chen, Jialuo, Zhang, Hongyuan, Liu, Jin, Han, Can, Fu, Kaiwen, Ji, Changkai, Cai, Xinxu, Hao, Jing, Zheng, Zhihao, Xu, Shi, Chen, Junqiang, Zhang, Qianni, Qian, Dahong, Wang, Shuai, Zhou, Huiyu

Sommario: “...) registered teams. To ensure algorithmic excellence and full transparency, we rigorously evaluated the valid...”
Testo

Semantic Soft Bootstrapping: Long Context Reasoning in LLMs without Reinforcement Learning di Mitra, Purbesh, Ulukus, Sennur

Sommario: “... optimization (GRPO), which is a commonly used RLVR algorithm. Our code is available at https://github.com...”
Testo

How Far are Modern Trackers from UAV-Anti-UAV? A Million-Scale Benchmark and New Baseline di Zhang, Chunhui, Liu, Li, Zhang, Zhipeng, Wang, Yong, Wen, Hao, Zhou, Xi, Ge, Shiming, Wang, Yanfeng

Sommario: “... of 50 modern deep tracking algorithms demonstrates that there is still significant room for improvement...”
Testo

TraPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning di Yang, Shenzhi, Zhu, Guangcheng, Zheng, Xing, MA, Yingfan, Chen, Zhongqi, Song, Bowen, Wang, Weiqiang, Zhao, Junbo, Chen, Gang, Wang, Haobo

Sommario: “... an effective policy optimization algorithm, TraPO, that identifies reliable unlabeled samples by matching...”
Testo

HERO-Sign: Hierarchical Tuning and Efficient Compiler-Time GPU Optimizations for SPHINCS+ Signature Generation di Zhou, Yaoyun, Wang, Qian

Sommario: “... algorithm that adapts fusion schemes to different GPU architectures. To further improve performance, HERO...”
Testo

SP-Rank: A Dataset for Ranked Preferences with Secondary Information di Hosseini, Hadi, Mandal, Debmalya, Puhan, Amrit

Sommario: “... algorithms that leverage both first-order preferences and second-order predictions in ranking tasks. Each...”
Testo

TowerMind: A Tower Defence Game Learning Environment and Benchmark for LLM as Agents di Wang, Dawei, Zhou, Chengming, Zhao, Di, Liu, Xinyuan, Ma, Marci Chi, Ushaw, Gary, Davison, Richard

Sommario: “... evaluate two classic reinforcement learning algorithms: Ape-X DQN and PPO. By offering a lightweight...”
Testo

Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems di Koike, Tomoki, Mohan, Prakash, de Frahan, Marc T. Henry, Bessac, Julie, Qian, Elizabeth

Sommario: “... access to the underlying code or full model operators, i.e., non-intrusively. Traditional OpInf operates...”
Testo

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning di Kim, Moo Jin, Gao, Yihuai, Lin, Tsung-Yi, Lin, Yen-Chen, Ge, Yunhao, Lam, Grace, Liang, Percy, Song, Shuran, Liu, Ming-Yu, Finn, Chelsea, Gu, Jinwei

Sommario: “...'s pretrained priors and core learning algorithm to capture complex action distributions. Additionally, Cosmos...”
Testo

EdgeMask-DG*: Learning Domain-Invariant Graph Structures via Adversarial Edge Masking di Bhattacharya, Rishabh, Manwani, Naresh

Sommario: “... algorithm where an edge masker learns to find worst-case continuous masks subject to a sparsity constraint...”
Testo

Mapping plasma properties of Cassiopeia A with XRISM/Resolve: a Bayesian analysis via UltraSPEX di Agarwal, Manan, Vink, Jacco, Gu, Liyi, Plucinsky, Paul P., Bamba, Aya, Sato, Toshiki, Rogantini, Daniele, Ohshiro, Yuken

Sommario: “... Bayesian framework that couples the SPEX plasma code with the UltraNest nested-sampling algorithm, yielding...”
Testo

MonoLoss: A Training Objective for Interpretable Monosemantic Representations di Nasiri-Sarvi, Ali, Nguyen, Anh Tien, Rivaz, Hassan, Samaras, Dimitris, Hosseini, Mahdi S.

Sommario: “... training and evaluation. We study a recent MonoScore metric and derive a single-pass algorithm...”
Testo

Unmasking Algorithmic Bias in Predictive Policing: A GAN-Based Simulation Framework with Multi-City Temporal Analysis di Barman, Pronob Kumar, Barman, Pronoy Kumar

Sommario: “...Predictive policing systems that direct patrol resources based on algorithmically generated crime...”
Testo

ProHunter: A Comprehensive APT Hunting System Based on Whole-System Provenance di Qiu, Xuebo, Lv, Mingqi, Zhang, Yimei, Zhu, Tiantian, Chen, Tieming

Sommario: “... strategies. To segment APT behaviors, a heuristic-driven threat graph sampling algorithm is designed, which...”
Testo

Cyclic light variations and accretion disk evolution in the LMC eclipsing binary OGLE-LMC-DPV-062 di Mennickent, R. E., Djurašević, G., Rosales, J. A., Garcés, J., Petrović, J., Schleicher, D. R. G., Soszyński, I.

Sommario: “... an optimized simplex algorithm to derive the best-fitting parameters of the stars, orbit, and disk. The MESA...”
Testo