{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/logistic-regression/papers/14","list_of":"/method/logistic-regression","method":"Logistic Regression","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":14,"pages_in_order":19,"rows_per_page":100,"rows":[1301,1400],"of":1886,"counts":{"archive_papers_tagged":1886,"with_a_code_link":461,"where_syntology_ran_a_sample":62,"not_listed_spam_title":0,"listed":1886,"listed_where_code_ran":62,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":48,"every_run_a_failure_of_syntologys_instrument":14,"listed_with_a_run_with_no_instrument_failure":48,"listed_every_run_a_failure_of_syntologys_instrument":14,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/logistic-regression","prev":"/method/logistic-regression/papers/13","next":"/method/logistic-regression/papers/15","papers":[{"paper":"/paper/prediction-of-homicides-in-urban-centers-a","slug":"prediction-of-homicides-in-urban-centers-a","title":"Prediction of Homicides in Urban Centers: A Machine Learning Approach","date":"2020-08-16","arxiv_id":"2008.06979","n_code_links":1,"syntology":null},{"paper":"/paper/logodet-3k-a-large-scale-image-dataset-for","slug":"logodet-3k-a-large-scale-image-dataset-for","title":"LogoDet-3K: A Large-Scale Image Dataset for Logo Detection","date":"2020-08-12","arxiv_id":"2008.05359","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-automated-end-to-end-framework-for","title":"An Automated, End-to-End Framework for Modeling Attacks From Vulnerability Descriptions","date":"2020-08-10","arxiv_id":"2008.04377","n_code_links":0,"syntology":null},{"paper":null,"slug":"evidence-of-predicting-early-signs-of","title":"Evidence of Predicting Early Signs of Corporate Bankruptcy Using Financial Ratios in the Indian Landscape","date":"2020-08-08","arxiv_id":"2008.04782","n_code_links":0,"syntology":null},{"paper":null,"slug":"gpu-accelerated-primal-learning-for-extremely","title":"GPU-Accelerated Primal Learning for Extremely Fast Large-Scale Classification","date":"2020-08-08","arxiv_id":"2008.03433","n_code_links":0,"syntology":null},{"paper":"/paper/two-step-penalised-logistic-regression-for","slug":"two-step-penalised-logistic-regression-for","title":"Two-step penalised logistic regression for multi-omic data with an application to cardiometabolic syndrome","date":"2020-08-01","arxiv_id":"2008.00235","n_code_links":1,"syntology":null},{"paper":null,"slug":"object-detection-and-tracking-algorithms-for","title":"Object Detection and Tracking Algorithms for Vehicle Counting: A Comparative Analysis","date":"2020-07-31","arxiv_id":"2007.16198","n_code_links":0,"syntology":null},{"paper":null,"slug":"communication-efficient-federated-learning-1","title":"Communication-Efficient Federated Learning via Optimal Client Sampling","date":"2020-07-30","arxiv_id":"2007.15197","n_code_links":0,"syntology":null},{"paper":null,"slug":"boosting-ant-colony-optimization-via-solution","title":"Boosting Ant Colony Optimization via Solution Prediction and Machine Learning","date":"2020-07-29","arxiv_id":"2008.04213","n_code_links":0,"syntology":null},{"paper":"/paper/predicting-multiple-icd-10-codes-from","slug":"predicting-multiple-icd-10-codes-from","title":"Predicting Multiple ICD-10 Codes from Brazilian-Portuguese Clinical Notes","date":"2020-07-29","arxiv_id":"2008.01515","n_code_links":1,"syntology":null},{"paper":"/paper/binary-search-and-first-order-gradient-based","slug":"binary-search-and-first-order-gradient-based","title":"Binary Search and First Order Gradient Based Method for Stochastic Optimization","date":"2020-07-27","arxiv_id":"2007.13413","n_code_links":1,"syntology":null},{"paper":"/paper/pp-yolo-an-effective-and-efficient","slug":"pp-yolo-an-effective-and-efficient","title":"PP-YOLO: An Effective and Efficient Implementation of Object Detector","date":"2020-07-23","arxiv_id":"2007.12099","n_code_links":5,"syntology":null},{"paper":null,"slug":"a-distributionally-robust-approach-to-fair","title":"A Distributionally Robust Approach to Fair Classification","date":"2020-07-18","arxiv_id":"2007.09530","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-approach-for-auxiliary-diagnosing-and","title":"Auxiliary Diagnosing Coronary Stenosis Using Machine Learning","date":"2020-07-16","arxiv_id":"2007.10316","n_code_links":0,"syntology":null},{"paper":null,"slug":"blockflow-an-accountable-and-privacy","title":"BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning","date":"2020-07-08","arxiv_id":"2007.03856","n_code_links":0,"syntology":null},{"paper":"/paper/slap-improving-physical-adversarial-examples","slug":"slap-improving-physical-adversarial-examples","title":"SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations","date":"2020-07-08","arxiv_id":"2007.04137","n_code_links":1,"syntology":null},{"paper":null,"slug":"winning-with-simple-learning-models-detecting","title":"Winning with Simple Learning Models: Detecting Earthquakes in Groningen, the Netherlands","date":"2020-07-08","arxiv_id":"2007.03924","n_code_links":0,"syntology":null},{"paper":"/paper/autonomous-and-cooperative-design-of-the","slug":"autonomous-and-cooperative-design-of-the","title":"Autonomous and cooperative design of the monitor positions for a team of UAVs to maximize the quantity and quality of detected objects","date":"2020-07-02","arxiv_id":"2007.01247","n_code_links":1,"syntology":null},{"paper":"/paper/can-we-achieve-more-with-less-exploring-data","slug":"can-we-achieve-more-with-less-exploring-data","title":"Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification","date":"2020-07-02","arxiv_id":"2007.00875","n_code_links":1,"syntology":null},{"paper":null,"slug":"covid-19-and-arabic-twitter-how-can-arab","title":"COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?","date":"2020-07-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"decentralized-stochastic-gradient-langevin","title":"Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo","date":"2020-07-01","arxiv_id":"2007.00590","n_code_links":0,"syntology":null},{"paper":null,"slug":"mapping-of-narrative-text-fields-to-icd-10","title":"Mapping of Narrative Text Fields To ICD-10 Codes Using Natural Language Processing and Machine Learning","date":"2020-07-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"opusfilter-a-configurable-parallel-corpus","title":"OpusFilter: A Configurable Parallel Corpus Filtering Toolbox","date":"2020-07-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"do-not-forget-interaction-predicting-fatality","title":"Do not forget interaction: Predicting fatality of COVID-19 patients using logistic regression","date":"2020-06-30","arxiv_id":"2006.16942","n_code_links":0,"syntology":null},{"paper":"/paper/tfnet-multi-semantic-feature-interaction-for","slug":"tfnet-multi-semantic-feature-interaction-for","title":"TFNet: Multi-Semantic Feature Interaction for CTR Prediction","date":"2020-06-29","arxiv_id":"2006.15939","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-customer-churn-in-world-of","title":"Predicting Customer Churn in World of Warcraft","date":"2020-06-28","arxiv_id":"2006.15735","n_code_links":0,"syntology":null},{"paper":null,"slug":"expandable-yolo-3d-object-detection-from-rgb","title":"Expandable YOLO: 3D Object Detection from RGB-D Images","date":"2020-06-26","arxiv_id":"2006.14837","n_code_links":0,"syntology":null},{"paper":null,"slug":"distribution-based-invariant-deep-networks","title":"Distribution-Based Invariant Deep Networks for Learning Meta-Features","date":"2020-06-24","arxiv_id":"2006.13708","n_code_links":0,"syntology":null},{"paper":"/paper/differentiable-segmentation-of-sequences","slug":"differentiable-segmentation-of-sequences","title":"Differentiable Segmentation of Sequences","date":"2020-06-23","arxiv_id":"2006.13105","n_code_links":1,"syntology":null},{"paper":null,"slug":"long-term-prediction-of-lane-change-maneuver","title":"Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron","date":"2020-06-23","arxiv_id":"2006.12769","n_code_links":0,"syntology":null},{"paper":null,"slug":"connecting-graph-convolutional-networks-and","title":"Connecting Graph Convolutional Networks and Graph-Regularized PCA","date":"2020-06-22","arxiv_id":"2006.12294","n_code_links":0,"syntology":null},{"paper":null,"slug":"electoral-david-vs-goliath-how-does-the","title":"Electoral David vs Goliath: How does the Spatial Concentration of Electors affect District-based Elections?","date":"2020-06-21","arxiv_id":"2006.11865","n_code_links":0,"syntology":null},{"paper":null,"slug":"langevin-dynamics-for-inverse-reinforcement","title":"Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms","date":"2020-06-20","arxiv_id":"2006.11674","n_code_links":0,"syntology":null},{"paper":"/paper/unsupervised-out-of-distribution-detection-2","slug":"unsupervised-out-of-distribution-detection-2","title":"Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation","date":"2020-06-18","arxiv_id":"2006.10712","n_code_links":1,"syntology":null},{"paper":null,"slug":"faster-secure-data-mining-via-distributed","title":"Faster Secure Data Mining via Distributed Homomorphic Encryption","date":"2020-06-17","arxiv_id":"2006.10091","n_code_links":0,"syntology":null},{"paper":null,"slug":"application-of-data-science-to-discover","title":"Application of Data Science to Discover Violence-Related Issues in Iraq","date":"2020-06-14","arxiv_id":"2006.07980","n_code_links":0,"syntology":null},{"paper":null,"slug":"few-shot-object-detection-on-remote-sensing","title":"Few-shot Object Detection on Remote Sensing Images","date":"2020-06-14","arxiv_id":"2006.07826","n_code_links":0,"syntology":null},{"paper":"/paper/v2e-from-video-frames-to-realistic-dvs-event","slug":"v2e-from-video-frames-to-realistic-dvs-event","title":"v2e: From Video Frames to Realistic DVS Events","date":"2020-06-13","arxiv_id":"2006.07722","n_code_links":3,"syntology":null},{"paper":null,"slug":"asymptotic-errors-for-teacher-student-convex","title":"Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula)","date":"2020-06-11","arxiv_id":"2006.06581","n_code_links":0,"syntology":null},{"paper":null,"slug":"weighted-lasso-estimates-for-sparse-logistic","title":"Weighted Lasso Estimates for Sparse Logistic Regression: Non-asymptotic Properties with Measurement Error","date":"2020-06-11","arxiv_id":"2006.06136","n_code_links":0,"syntology":null},{"paper":null,"slug":"robustified-multivariate-regression-and","title":"Robustified Multivariate Regression and Classification Using Distributionally Robust Optimization under the Wasserstein Metric","date":"2020-06-10","arxiv_id":"2006.06090","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-quantification-of-ct-patterns","title":"Machine Learning Automatically Detects COVID-19 using Chest CTs in a Large Multicenter Cohort","date":"2020-06-09","arxiv_id":"2006.04998","n_code_links":0,"syntology":null},{"paper":"/paper/interpretable-signal-analysis-with-knockoffs","slug":"interpretable-signal-analysis-with-knockoffs","title":"Interpretable Classification of Bacterial Raman Spectra with Knockoff Wavelets","date":"2020-06-08","arxiv_id":"2006.04937","n_code_links":1,"syntology":null},{"paper":"/paper/black-box-explanation-of-object-detectors-via","slug":"black-box-explanation-of-object-detectors-via","title":"Black-box Explanation of Object Detectors via Saliency Maps","date":"2020-06-05","arxiv_id":"2006.03204","n_code_links":2,"syntology":{"ran":3,"of":3,"n_ran_checked":2,"n_instrument":1,"unverified":0,"pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/newb-200000-sentences-for-political-bias","slug":"newb-200000-sentences-for-political-bias","title":"NewB: 200,000+ Sentences for Political Bias Detection","date":"2020-06-04","arxiv_id":"2006.03051","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-refinements-on-yolov3-for-real-time","title":"Deep Learning Methods for Real-time Detection and Analysis of Wagner Ulcer Classification System","date":"2020-06-03","arxiv_id":"2006.02322","n_code_links":0,"syntology":null},{"paper":null,"slug":"countering-hate-on-social-media-large-scale","title":"Countering hate on social media: Large scale classification of hate and counter speech","date":"2020-06-02","arxiv_id":"2006.01974","n_code_links":0,"syntology":null},{"paper":null,"slug":"logistic-regression-for-massive-data-with","title":"Logistic Regression for Massive Data with Rare Events","date":"2020-06-01","arxiv_id":"2006.00683","n_code_links":0,"syntology":null},{"paper":null,"slug":"bpgc-at-semeval-2020-task-11-propaganda","title":"BPGC at SemEval-2020 Task 11: Propaganda Detection in News Articles with Multi-Granularity Knowledge Sharing and Linguistic Features based Ensemble Learning","date":"2020-05-31","arxiv_id":"2006.00593","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-problem-statements-in-peer","title":"Detecting Problem Statements in Peer Assessments","date":"2020-05-30","arxiv_id":"2006.04532","n_code_links":0,"syntology":null},{"paper":"/paper/poly-yolo-higher-speed-more-precise-detection","slug":"poly-yolo-higher-speed-more-precise-detection","title":"Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3","date":"2020-05-27","arxiv_id":"2005.13243","n_code_links":2,"syntology":null},{"paper":null,"slug":"using-machine-learning-to-forecast-future","title":"Using Machine Learning to Forecast Future Earnings","date":"2020-05-26","arxiv_id":"2005.13995","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-machine-learning-approach-to-using-quality","title":"A machine learning approach to using Quality-of-Life patient scores in guiding prostate radiation therapy dosing","date":"2020-05-22","arxiv_id":"2005.10951","n_code_links":0,"syntology":null},{"paper":null,"slug":"secure-and-differentially-private-bayesian","title":"Secure and Differentially Private Bayesian Learning on Distributed Data","date":"2020-05-22","arxiv_id":"2005.11007","n_code_links":0,"syntology":null},{"paper":null,"slug":"covid-19-public-sentiment-insights-and","title":"COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification","date":"2020-05-21","arxiv_id":"2005.10898","n_code_links":0,"syntology":null},{"paper":null,"slug":"swift-super-fast-and-robust-privacy","title":"SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning","date":"2020-05-20","arxiv_id":"2005.10296","n_code_links":0,"syntology":null},{"paper":null,"slug":"blaze-blazing-fast-privacy-preserving-machine","title":"BLAZE: Blazing Fast Privacy-Preserving Machine Learning","date":"2020-05-18","arxiv_id":"2005.09042","n_code_links":0,"syntology":null},{"paper":null,"slug":"nit-agartala-nlp-team-at-semeval-2020-task-8","title":"NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor","date":"2020-05-14","arxiv_id":"2005.06943","n_code_links":0,"syntology":null},{"paper":null,"slug":"apple-defect-detection-using-deep-learning","title":"Apple Defect Detection Using Deep Learning Based Object Detection For Better Post Harvest Handling","date":"2020-05-12","arxiv_id":"2005.06089","n_code_links":0,"syntology":null},{"paper":null,"slug":"perturbing-inputs-to-prevent-model-stealing","title":"Perturbing Inputs to Prevent Model Stealing","date":"2020-05-12","arxiv_id":"2005.05823","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-latent-communities-in-network","title":"Detecting Latent Communities in Network Formation Models","date":"2020-05-07","arxiv_id":"2005.03226","n_code_links":0,"syntology":null},{"paper":"/paper/the-strong-screening-rule-for-slope","slug":"the-strong-screening-rule-for-slope","title":"The Strong Screening Rule for SLOPE","date":"2020-05-07","arxiv_id":"2005.03730","n_code_links":1,"syntology":null},{"paper":null,"slug":"automatic-detection-and-recognition-of","title":"Automatic Detection and Recognition of Individuals in Patterned Species","date":"2020-05-06","arxiv_id":"2005.02905","n_code_links":0,"syntology":null},{"paper":null,"slug":"one-step-regression-and-classification-with","title":"One-step regression and classification with crosspoint resistive memory arrays","date":"2020-05-05","arxiv_id":"2005.01988","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-eye-disease-classification-method","title":"Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique","date":"2020-05-04","arxiv_id":"2005.01433","n_code_links":0,"syntology":null},{"paper":null,"slug":"ensemble-forecasting-for-intraday-electricity","title":"Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories","date":"2020-05-04","arxiv_id":"2005.01365","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-fact-checking-of-claims-from","title":"Automated Fact-Checking of Claims from Wikipedia","date":"2020-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/bag-tag-em-a-new-dutch-stemmer","slug":"bag-tag-em-a-new-dutch-stemmer","title":"Bag \\& Tag'em - A New Dutch Stemmer","date":"2020-05-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"clfd-a-novel-vectorization-technique-and-its","title":"CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection","date":"2020-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-of-manual-and-non-manual","title":"Evaluation of Manual and Non-manual Components for Sign Language Recognition","date":"2020-05-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/performance-accuration-method-of-machine","slug":"performance-accuration-method-of-machine","title":"Performance Accuration Method of Machine Learning for Diabetes Prediction","date":"2020-05-01","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":null,"slug":"improving-vertical-positioning-accuracy-with","title":"Improving Vertical Positioning Accuracy with the Weighted Multinomial Logistic Regression Classifier","date":"2020-04-29","arxiv_id":"2004.13909","n_code_links":0,"syntology":null},{"paper":"/paper/neural-additive-models-interpretable-machine","slug":"neural-additive-models-interpretable-machine","title":"Neural Additive Models: Interpretable Machine Learning with Neural Nets","date":"2020-04-29","arxiv_id":"2004.13912","n_code_links":8,"syntology":{"ran":26,"of":33,"n_ran_checked":26,"n_instrument":0,"unverified":7,"pointer_only":14,"phrase":"26 ran (of which 14 constructed an object rather than computing a result; 26 with no instrument failure: 5 honoured, 0 violated, 21 with no contract checked; 0 where Syntology's instrument failed) · 7 unverified","official":{"repos":["lemeln/nam"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"interpretable-multi-task-deep-neural-networks","title":"Dynamic Predictions of Postoperative Complications from Explainable, Uncertainty-Aware, and Multi-Task Deep Neural Networks","date":"2020-04-27","arxiv_id":"2004.12551","n_code_links":0,"syntology":null},{"paper":null,"slug":"classification-of-cuisines-from-sequentially","title":"Classification of Cuisines from Sequentially Structured Recipes","date":"2020-04-26","arxiv_id":"2004.14165","n_code_links":0,"syntology":null},{"paper":"/paper/yolov4-optimal-speed-and-accuracy-of-object","slug":"yolov4-optimal-speed-and-accuracy-of-object","title":"YOLOv4: Optimal Speed and Accuracy of Object Detection","date":"2020-04-23","arxiv_id":"2004.10934","n_code_links":223,"syntology":{"ran":142,"of":184,"n_ran_checked":133,"n_instrument":9,"unverified":42,"pointer_only":21,"phrase":"142 ran (of which 0 constructed an object rather than computing a result; 133 with no instrument failure: 6 honoured, 0 violated, 127 with no contract checked; 9 where Syntology's instrument failed) · 42 unverified","official":{"repos":["AlexeyAB/darknet"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"counterfactual-confounding-adjustment-for","title":"Causality-aware counterfactual confounding adjustment for feature representations learned by deep models","date":"2020-04-20","arxiv_id":"2004.09466","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-nucleation-near-the-spinodal-in","title":"Predicting nucleation near the spinodal in the Ising model using machine learning","date":"2020-04-20","arxiv_id":"2004.09575","n_code_links":0,"syntology":null},{"paper":null,"slug":"asymmetrically-vertical-federated-learning","title":"Asymmetrical Vertical Federated Learning","date":"2020-04-16","arxiv_id":"2004.07427","n_code_links":0,"syntology":null},{"paper":"/paper/sentiment-analysis-of-yelp-reviews-a","slug":"sentiment-analysis-of-yelp-reviews-a","title":"Sentiment Analysis of Yelp Reviews: A Comparison of Techniques and Models","date":"2020-04-15","arxiv_id":"2004.13851","n_code_links":1,"syntology":null},{"paper":"/paper/deep-learning-models-for-multilingual-hate","slug":"deep-learning-models-for-multilingual-hate","title":"Deep Learning Models for Multilingual Hate Speech Detection","date":"2020-04-14","arxiv_id":"2004.06465","n_code_links":3,"syntology":null},{"paper":null,"slug":"wqt-and-dg-yolo-towards-domain-generalization","title":"WQT and DG-YOLO: towards domain generalization in underwater object detection","date":"2020-04-14","arxiv_id":"2004.06333","n_code_links":0,"syntology":null},{"paper":null,"slug":"secret-sharing-based-secure-regressions-with","title":"Secret Sharing based Secure Regressions with Applications","date":"2020-04-10","arxiv_id":"2004.04898","n_code_links":0,"syntology":null},{"paper":null,"slug":"file-classification-based-on-spiking-neural","title":"File Classification Based on Spiking Neural Networks","date":"2020-04-08","arxiv_id":"2004.03953","n_code_links":0,"syntology":null},{"paper":null,"slug":"improved-yolov3-object-classification-in","title":"Improved YOLOv3 Object Classification in Intelligent Transportation System","date":"2020-04-08","arxiv_id":"2004.03948","n_code_links":0,"syntology":null},{"paper":"/paper/increasing-the-inference-and-learning-speed","slug":"increasing-the-inference-and-learning-speed","title":"Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing","date":"2020-04-07","arxiv_id":"2004.03188","n_code_links":1,"syntology":null},{"paper":"/paper/effect-of-annotation-errors-on-drone","slug":"effect-of-annotation-errors-on-drone","title":"Effect of Annotation Errors on Drone Detection with YOLOv3","date":"2020-04-02","arxiv_id":"2004.01059","n_code_links":1,"syntology":null},{"paper":null,"slug":"optimizing-the-reliability-of-a-bank-with","title":"Optimizing the reliability of a bank with Logistic Regression and Particle Swarm Optimization","date":"2020-03-31","arxiv_id":"2004.11122","n_code_links":0,"syntology":null},{"paper":null,"slug":"detection-of-floss-version-release-events","title":"Is it feasible to detect FLOSS version release events from textual messages? A case study on Stack Overflow","date":"2020-03-30","arxiv_id":"2003.14257","n_code_links":0,"syntology":null},{"paper":null,"slug":"dimension-independent-generalization-error","title":"Dimension Independent Generalization Error by Stochastic Gradient Descent","date":"2020-03-25","arxiv_id":"2003.11196","n_code_links":0,"syntology":null},{"paper":null,"slug":"tracer-a-framework-for-facilitating-accurate","title":"TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications","date":"2020-03-24","arxiv_id":"2003.12012","n_code_links":0,"syntology":null},{"paper":null,"slug":"algorithms-for-non-stationary-generalized","title":"Algorithms for Non-Stationary Generalized Linear Bandits","date":"2020-03-23","arxiv_id":"2003.10113","n_code_links":0,"syntology":null},{"paper":"/paper/multipath-computation-offloading-for-mobile","slug":"multipath-computation-offloading-for-mobile","title":"Multipath Computation Offloading for Mobile Augmented Reality","date":"2020-03-23","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"multilayer-dense-connections-for-hierarchical","title":"Multilayer Dense Connections for Hierarchical Concept Classification","date":"2020-03-19","arxiv_id":"2003.09015","n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-estimation-in-cancer-survival","title":"Uncertainty Estimation in Cancer Survival Prediction","date":"2020-03-19","arxiv_id":"2003.08573","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-twitter-sentiment-analysis-model-with","title":"A Novel Twitter Sentiment Analysis Model with Baseline Correlation for Financial Market Prediction with Improved Efficiency","date":"2020-03-18","arxiv_id":"2003.08137","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-improper-learning-for-online","title":"Efficient improper learning for online logistic regression","date":"2020-03-18","arxiv_id":"2003.08109","n_code_links":0,"syntology":null},{"paper":null,"slug":"logistic-regression-with-peer-group-effects","title":"Logistic-Regression with peer-group effects via inference in higher order Ising models","date":"2020-03-18","arxiv_id":"2003.08259","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-precisely-xtreme-multi-channel-hybrid","title":"A Precisely Xtreme-Multi Channel Hybrid Approach For Roman Urdu Sentiment Analysis","date":"2020-03-11","arxiv_id":"2003.05443","n_code_links":0,"syntology":null},{"paper":null,"slug":"amortized-variance-reduction-for-doubly","title":"Amortized variance reduction for doubly stochastic objectives","date":"2020-03-09","arxiv_id":"2003.04125","n_code_links":0,"syntology":null}],"record_sha256":"6d9d8ed508c8b45056023ec552829c1d8444ebb5d1c5f050eaa7143912ffdb71","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}