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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 6751–6800 of 10033 papers

TitleStatusHype
Learning dynamic polynomial proofs—0
A Novel Hyperparameter-free Approach to Decision Tree Construction that Avoids Overfitting by Design—0
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis—0
Effective LHC measurements with matrix elements and machine learning—0
Algorithmically generating new algebraic features of polynomial systems for machine learning—0
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning—0
Hybrid Machine Learning Forecasts for the FIFA Women's World Cup 2019—0
Attractive versus truncated repulsive supercooled liquids: The dynamics is encoded in the pair correlation function—0
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference—0
Stochastic Generalized Adversarial Label Learning—0
Disparate Vulnerability to Membership Inference AttacksCode0
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal InferenceCode0
Neural Models of Text Normalization for Speech Applications—0
SO(8) Supergravity and the Magic of Machine Learning—0
Linguistic Analysis of Schizophrenia in Reddit Posts—0
The R2I\_LIS Team Proposes Majority Vote for VarDial's MRC Task—0
Using natural conversations to classify autism with limited data: Age matters—0
Towards the Data-driven System for Rhetorical Parsing of Russian Texts—0
UVA Wahoos at SemEval-2019 Task 6: Hate Speech Identification using Ensemble Machine Learning—0
UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post's Nesting and Syntax Information for Rumor Stance Classification—0
RGCL-WLV at SemEval-2019 Task 12: Toponym Detection—0
Team Taurus at SemEval-2019 Task 9: Expert-informed pattern recognition for suggestion mining—0
SSN\_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches—0
E-LSTM at SemEval-2019 Task 3: Semantic and Sentimental Features Retention for Emotion Detection in Text—0
Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation—0
Litigation Analytics: Extracting and querying motions and orders from US federal courts—0
Nikolov-Radivchev at SemEval-2019 Task 6: Offensive Tweet Classification with BERT and Ensembles—0
Automated Machine Learning with Monte-Carlo Tree SearchCode0
Patch LearningCode0
Polynomial Representation for Persistence Diagram—0
Transferable AutoML by Model Sharing Over Grouped Datasets—0
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice—0
Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version)—0
Real-Time Adversarial AttacksCode0
Fast Online "Next Best Offers" using Deep Learning—0
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models—0
GENO -- GENeric Optimization for Classical Machine Learning—0
IoT Network Security from the Perspective of Adversarial Deep Learning—0
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing—0
Evaluating Memento Service Optimizations—0
Do Human Rationales Improve Machine Explanations?—0
Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Meniere's Disease—0
Meta Dropout: Learning to Perturb Features for GeneralizationCode1
Application of Different Simulated Spectral Data and Machine Learning to Estimate the Chlorophyll a Concentration of Several Inland Waters—0
Complex-valued neural networks for machine learning on non-stationary physical dataCode0
Categorization of Program Regions for Agile Compilation using Machine Learning and Hardware Support—0
Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approachCode0
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems—0
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward—0
A Topology Layer for Machine LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified