SOTAVerified

BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 4501–4525 of 10033 papers

TitleStatusHype
Human Activity Recognition models using Limited Consumer Device Sensors and Machine Learning—0
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey—0
Communication Efficiency in Federated Learning: Achievements and Challenges—0
Human Activity Recognition using Recurrent Neural Networks—0
Human-aided Multi-Entity Bayesian Networks Learning from Relational Data—0
Human-Algorithm Interaction Biases in the Big Data Cycle: A Markov Chain Iterated Learning Framework—0
Classifying Single-Trial EEG during Motor Imagery with a Small Training Set—0
Human-Centered Artificial Intelligence and Machine Learning—0
Communication Efficient Distributed Machine Learning with the Parameter Server—0
Human experts vs. machines in taxa recognition—0
Human Gist Processing Augments Deep Learning Breast Cancer Risk Assessment—0
Human-in-the-Loop Design Cycles -- A Process Framework that Integrates Design Sprints, Agile Processes, and Machine Learning with Humans—0
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data—0
Human-like machine learning: limitations and suggestions—0
Human-Machine Inference Networks For Smart Decision Making: Opportunities and Challenges—0
Human-robot collaboration and machine learning: a systematic review of recent research—0
Humans Learn Using Manifolds, Reluctantly—0
Human vs. supervised machine learning: Who learns patterns faster?—0
Human Wellbeing and Machine Learning—0
A Novel Multi-Step Finite-State Automaton for Arbitrarily Deterministic Tsetlin Machine Learning—0
Hybrid Active Inference—0
Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes—0
Gravitational wave surrogates through automated machine learning—0
Distributed Machine Learning in D2D-Enabled Heterogeneous Networks: Architectures, Performance, and Open Challenges—0
Gravilon: Applications of a New Gradient Descent Method to Machine Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified