Summary of Partially Observable Contextual Bandits with Linear Payoffs, by Sihan Zeng et al.
Partially Observable Contextual Bandits with Linear Payoffsby Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra GaneshFirst…
Summary of Fedne: Surrogate-assisted Federated Neighbor Embedding For Dimensionality Reduction, by Ziwei Li et al.
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reductionby Ziwei Li, Xiaoqi Wang, Hong-You Chen, Han-Wei…
Summary of Unlocking Nace Classification Embeddings with Openai For Enhanced Analysis and Processing, by Andrea Vidali et al.
Unlocking NACE Classification Embeddings with OpenAI for Enhanced Analysis and Processingby Andrea Vidali, Nicola Jean,…
Summary of Oneencoder: a Lightweight Framework For Progressive Alignment Of Modalities, by Bilal Faye et al.
OneEncoder: A Lightweight Framework for Progressive Alignment of Modalitiesby Bilal Faye, Hanane Azzag, Mustapha LebbahFirst…
Summary of A Reinforcement Learning Environment For Automatic Code Optimization in the Mlir Compiler, by Nazim Bendib et al.
A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compilerby Nazim Bendib, Iheb…
Summary of A Hybrid Multi-factor Network with Dynamic Sequence Modeling For Early Warning Of Intraoperative Hypotension, by Mingyue Cheng and Jintao Zhang and Zhiding Liu and Chunli Liu and Yanhu Xie
A Hybrid Multi-Factor Network with Dynamic Sequence Modeling for Early Warning of Intraoperative Hypotensionby Mingyue…
Summary of Monokan: Certified Monotonic Kolmogorov-arnold Network, by Alejandro Polo-molina et al.
MonoKAN: Certified Monotonic Kolmogorov-Arnold Networkby Alejandro Polo-Molina, David Alfaya, Jose PortelaFirst submitted to arxiv on:…
Summary of Improve Machine Learning Carbon Footprint Using Parquet Dataset Format and Mixed Precision Training For Regression Models — Part Ii, by Andrew Antonopoulos
Improve Machine Learning carbon footprint using Parquet dataset format and Mixed Precision training for regression…
Summary of Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approach, by Debarpan Bhattacharya et al.
Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approachby Debarpan Bhattacharya, Amir H. Poorjam, Deepak Mittal,…
Summary of Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study, by Nikolai Merkel et al.
Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Studyby Nikolai Merkel, Pierre…