{"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":"/task/active-learning/papers/30","list_of":"/task/active-learning","task":"Active Learning","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":30,"pages_in_order":31,"rows_per_page":100,"rows":[2901,3000],"of":3073,"counts":{"archive_papers_tagged":3073,"with_a_code_link":913,"where_syntology_ran_a_sample":195,"not_listed_spam_title":0,"listed":3073,"listed_where_code_ran":195,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":164,"every_run_a_failure_of_syntologys_instrument":31,"listed_with_a_run_with_no_instrument_failure":164,"listed_every_run_a_failure_of_syntologys_instrument":31,"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":"/task/active-learning","prev":"/task/active-learning/papers/29","next":"/task/active-learning/papers/31","papers":[{"url":null,"slug":"judging-the-quality-of-automatically","title":"Judging the Quality of Automatically Generated Gap-fill Question using Active Learning","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"narrowing-the-loop-integration-of-resources","title":"Narrowing the Loop: Integration of Resources and Linguistic Dataset Development with Interactive Machine Learning","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"strat-egies-de-s-election-des-exemples-pour-l","title":"Strat\\'egies de s\\'election des exemples pour l'apprentissage actif avec des champs al\\'eatoires conditionnels","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"what-ive-learned-about-annotating-informal","title":"What I've learned about annotating informal text (and why you shouldn't take my word for it)","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-with-a-drifting-target-concept","title":"Learning with a Drifting Target Concept","date":"2015-05-20","arxiv_id":"1505.05215","repositories_listed":0,"syntology":null},{"url":null,"slug":"algorithmic-connections-between-active","title":"Algorithmic Connections Between Active Learning and Stochastic Convex Optimization","date":"2015-05-15","arxiv_id":"1505.04214","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-analysis-of-active-learning-with-uniform","title":"An Analysis of Active Learning With Uniform Feature Noise","date":"2015-05-15","arxiv_id":"1505.04215","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-sense-annotation","title":"Active learning for sense annotation","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-with-rationales-for-text","title":"Active Learning with Rationales for Text Classification","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"removing-the-training-wheels-a-coreference","title":"Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"social-media-predictive-analytics","title":"Social Media Predictive Analytics","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-subquery-evaluation-for-active","title":"Hierarchical Subquery Evaluation for Active Learning on a Graph","date":"2015-04-30","arxiv_id":"1504.08219","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-active-learning-based-approach-for","title":"An Active Learning Based Approach For Effective Video Annotation And Retrieval","date":"2015-04-27","arxiv_id":"1504.07004","repositories_listed":0,"syntology":null},{"url":null,"slug":"autonomy-and-reliability-of-continuous-active","title":"Autonomy and Reliability of Continuous Active Learning for Technology-Assisted Review","date":"2015-04-26","arxiv_id":"1504.06868","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-of-stopping-active-learning-based-on","title":"Analysis of Stopping Active Learning based on Stabilizing Predictions","date":"2015-04-23","arxiv_id":"1504.06329","repositories_listed":0,"syntology":null},{"url":null,"slug":"deciding-when-to-stop-efficient-stopping-of","title":"Deciding when to stop: Efficient stopping of active learning guided drug-target prediction","date":"2015-04-09","arxiv_id":"1504.02406","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-vision-of-collaborative-active-learning","title":"A New Vision of Collaborative Active Learning","date":"2015-04-01","arxiv_id":"1504.00284","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-model-aggregation-via-stochastic","title":"Active Model Aggregation via Stochastic Mirror Descent","date":"2015-03-28","arxiv_id":"1503.08363","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-network-based-active-learning-in","title":"Neural Network-Based Active Learning in Multivariate Calibration","date":"2015-03-19","arxiv_id":"1503.05831","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-properties-are-desirable-from-an","title":"What Properties are Desirable from an Electron Microscopy Segmentation Algorithm","date":"2015-03-18","arxiv_id":"1503.05430","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-learning-of-linear-separators-under","title":"Efficient Learning of Linear Separators under Bounded Noise","date":"2015-03-12","arxiv_id":"1503.03594","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-active-learning-with-feature-selection","title":"Joint Active Learning with Feature Selection via CUR Matrix Decomposition","date":"2015-03-04","arxiv_id":"1503.01239","repositories_listed":0,"syntology":null},{"url":null,"slug":"just-sort-it-a-simple-and-effective-approach","title":"Just Sort It! A Simple and Effective Approach to Active Preference Learning","date":"2015-02-19","arxiv_id":"1502.05556","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaussian-process-models-for-hrtf-based-sound","title":"Gaussian Process Models for HRTF based Sound-Source Localization and Active-Learning","date":"2015-02-11","arxiv_id":"1502.03163","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-optimal-active-learning-via-model","title":"Estimating Optimal Active Learning via Model Retraining Improvement","date":"2015-02-05","arxiv_id":"1502.01664","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-descent-analysis-of-representation","title":"Stochastic Descent Analysis of Representation Learning Algorithms","date":"2014-12-18","arxiv_id":"1412.5744","repositories_listed":0,"syntology":null},{"url":null,"slug":"visual-causal-feature-learning","title":"Visual Causal Feature Learning","date":"2014-12-07","arxiv_id":"1412.2309","repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-and-selecting-relevant-corpora-for","title":"Extracting and Selecting Relevant Corpora for Domain Adaptation in MT","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"needle-in-a-haystack-reducing-the-costs-of","title":"Needle in a Haystack: Reducing the Costs of Annotating Rare-Class Instances in Imbalanced Datasets","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sampling-for-inference-in-probabilistic","title":"Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature","date":"2014-11-03","arxiv_id":"1411.0439","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-regression-by-stratification","title":"Active Regression by Stratification","date":"2014-10-22","arxiv_id":"1410.5920","repositories_listed":0,"syntology":null},{"url":null,"slug":"bucking-the-trend-large-scale-cost-focused","title":"Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation","date":"2014-10-21","arxiv_id":"1410.5877","repositories_listed":0,"syntology":null},{"url":null,"slug":"minimax-analysis-of-active-learning","title":"Minimax Analysis of Active Learning","date":"2014-10-03","arxiv_id":"1410.0996","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-experimental-comparison-of-active-learning","title":"An Experimental Comparison of Active Learning Strategies for Partially Labeled Sequences","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-distant-and-partial-supervision-for","title":"Combining Distant and Partial Supervision for Relation Extraction","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"formalizing-word-sampling-for-vocabulary","title":"Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-dictionary-learning-in-sparse","title":"Active Dictionary Learning in Sparse Representation Based Classification","date":"2014-09-19","arxiv_id":"1409.5763","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-method-for-stopping-active-learning-based","title":"A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping","date":"2014-09-17","arxiv_id":"1409.5165","repositories_listed":0,"syntology":null},{"url":null,"slug":"taking-into-account-the-differences-between","title":"Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets","date":"2014-09-17","arxiv_id":"1409.4835","repositories_listed":0,"syntology":null},{"url":null,"slug":"ice-enabling-non-experts-to-build-models","title":"ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems","date":"2014-09-16","arxiv_id":"1409.4814","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-metric-learning-from-relative","title":"Active Metric Learning from Relative Comparisons","date":"2014-09-15","arxiv_id":"1409.4155","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-approach-to-reducing-annotation-costs-for","title":"An Approach to Reducing Annotation Costs for BioNLP","date":"2014-09-12","arxiv_id":"1409.3881","repositories_listed":0,"syntology":null},{"url":null,"slug":"exponentiated-gradient-exploration-for-active","title":"Exponentiated Gradient Exploration for Active Learning","date":"2014-08-10","arxiv_id":"1408.2196","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-does-active-learning-work","title":"When does Active Learning Work?","date":"2014-08-06","arxiv_id":"1408.1319","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-in-noisy-conditions-for","title":"Active Learning in Noisy Conditions for Spoken Language Understanding","date":"2014-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"method51-for-mining-insight-from-social-media","title":"Method51 for Mining Insight from Social Media Datasets","date":"2014-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-annotation-efforts-to-build","title":"Optimizing annotation efforts to build reliable annotated corpora for training statistical models","date":"2014-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"targeting-optimal-active-learning-via-example","title":"Targeting Optimal Active Learning via Example Quality","date":"2014-07-30","arxiv_id":"1407.8042","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-nonparametric-crowdsourcing","title":"Bayesian Nonparametric Crowdsourcing","date":"2014-07-18","arxiv_id":"1407.5017","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-disagreement-based-agnostic-active","title":"Beyond Disagreement-based Agnostic Active Learning","date":"2014-07-10","arxiv_id":"1407.2657","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-privately-with-labeled-and-unlabeled","title":"Learning Privately with Labeled and Unlabeled Examples","date":"2014-07-10","arxiv_id":"1407.2662","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-and-best-response-dynamics","title":"Active Learning and Best-Response Dynamics","date":"2014-06-25","arxiv_id":"1406.6633","repositories_listed":0,"syntology":null},{"url":null,"slug":"noise-adaptive-margin-based-active-learning","title":"Noise-adaptive Margin-based Active Learning and Lower Bounds under Tsybakov Noise Condition","date":"2014-06-20","arxiv_id":"1406.5383","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-with-constrained-topic-model","title":"Active Learning with Constrained Topic Model","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-with-efficient-feature","title":"Active Learning with Efficient Feature Weighting Methods for Improving Data Quality and Classification Accuracy","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-annotation-suggestions-and-custom","title":"Automatic Annotation Suggestions and Custom Annotation Layers in WebAnno","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-comparing-image-pairs-setwise-active","title":"Beyond Comparing Image Pairs: Setwise Active Learning for Relative Attributes","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bilingual-active-learning-for-relation","title":"Bilingual Active Learning for Relation Classification via Pseudo Parallel Corpora","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"design-of-an-active-learning-system-with","title":"Design of an Active Learning System with Human Correction for Content Analysis","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"difficult-cases-from-data-to-learning-and","title":"Difficult Cases: From Data to Learning, and Back","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-classification-based-natural","title":"Improving Classification-Based Natural Language Understanding with Non-Expert Annotation","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-activity-modeling-and-recognition","title":"Incremental Activity Modeling and Recognition in Streaming Videos","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-features-in-active-machine","title":"Optimizing Features in Active Machine Learning for Complex Qualitative Content Analysis","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"parallel-fda5-for-fast-deployment-of-accurate","title":"Parallel FDA5 for Fast Deployment of Accurate Statistical Machine Translation Systems","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantics-for-large-scale-multimedia-new","title":"Semantics for Large-Scale Multimedia: New Challenges for NLP","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"structuring-operative-notes-using-active","title":"Structuring Operative Notes using Active Learning","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-quality-based-active-sample-selection","title":"A Quality-based Active Sample Selection Strategy for Statistical Machine Translation","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"focusing-annotation-for-semantic-role","title":"Focusing Annotation for Semantic Role Labeling","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-resource-addition-dictionary-or","title":"Language Resource Addition: Dictionary or Corpus?","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-undirected-graphical","title":"Active Learning for Undirected Graphical Model Selection","date":"2014-04-13","arxiv_id":"1404.3418","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-compression-technique-for-analyzing","title":"A Compression Technique for Analyzing Disagreement-Based Active Learning","date":"2014-04-05","arxiv_id":"1404.1504","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-post-editing-based","title":"Active Learning for Post-Editing Based Incrementally Retrained MT","date":"2014-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"confidence-based-active-learning-methods-for","title":"Confidence-based Active Learning Methods for Machine Translation","date":"2014-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-with-active-learning-for","title":"Domain Adaptation with Active Learning for Coreference Resolution","date":"2014-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-autonomous-intelligent","title":"Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction","date":"2014-03-06","arxiv_id":"1403.1497","repositories_listed":0,"syntology":null},{"url":null,"slug":"near-optimal-bayesian-active-learning-for","title":"Near Optimal Bayesian Active Learning for Decision Making","date":"2014-02-24","arxiv_id":"1402.5886","repositories_listed":0,"syntology":null},{"url":null,"slug":"selective-sampling-with-drift","title":"Selective Sampling with Drift","date":"2014-02-17","arxiv_id":"1402.4084","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-activity-recognition-using-smartphone","title":"Human Activity Recognition using Smartphone","date":"2014-01-30","arxiv_id":"1401.8212","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-supervised-anomaly-detection","title":"Toward Supervised Anomaly Detection","date":"2014-01-23","arxiv_id":"1401.6424","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-active-learning-approach-for-jointly","title":"An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data","date":"2014-01-16","arxiv_id":"1401.3836","repositories_listed":0,"syntology":null},{"url":null,"slug":"segmentation-for-efficient-supervised","title":"Segmentation for Efficient Supervised Language Annotation with an Explicit Cost-Utility Tradeoff","date":"2014-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-discovery-of-network-roles-for","title":"Active Discovery of Network Roles for Predicting the Classes of Network Nodes","date":"2013-12-27","arxiv_id":"1312.7258","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-player-modelling","title":"Active Player Modelling","date":"2013-12-10","arxiv_id":"1312.2936","repositories_listed":0,"syntology":null},{"url":null,"slug":"-optimality-for-active-learning-on-gaussian","title":"Σ-Optimality for Active Learning on Gaussian Random Fields","date":"2013-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-probabilistic-hypotheses","title":"Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion","date":"2013-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"buy-in-bulk-active-learning","title":"Buy-in-Bulk Active Learning","date":"2013-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-structured-active-learning","title":"Latent Structured Active Learning","date":"2013-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-active-learning-algorithms","title":"Statistical Active Learning Algorithms","date":"2013-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recommending-with-an-agenda-active-learning","title":"Recommending with an Agenda: Active Learning of Private Attributes using Matrix Factorization","date":"2013-11-26","arxiv_id":"1311.6802","repositories_listed":0,"syntology":null},{"url":null,"slug":"beating-the-minimax-rate-of-active-learning","title":"Beating the Minimax Rate of Active Learning with Prior Knowledge","date":"2013-11-19","arxiv_id":"1311.4803","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-dependency-parsing-by-a","title":"Active Learning for Dependency Parsing by A Committee of Parsers","date":"2013-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"para-active-learning","title":"Para-active learning","date":"2013-10-30","arxiv_id":"1310.8243","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-of-linear-embeddings-for","title":"Active Learning of Linear Embeddings for Gaussian Processes","date":"2013-10-24","arxiv_id":"1310.6740","repositories_listed":0,"syntology":null},{"url":null,"slug":"advances-in-hyperspectral-image","title":"Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods","date":"2013-10-18","arxiv_id":"1310.5107","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-active-learning-framework-for","title":"An Efficient Active Learning Framework for New Relation Types","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bootstrapping-phrase-based-statistical","title":"Bootstrapping Phrase-based Statistical Machine Translation via WSD Integration","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-missing-annotation-disagreement","title":"Detecting Missing Annotation Disagreement using Eye Gaze Information","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reserved-self-training-a-semi-supervised","title":"Reserved Self-training: A Semi-supervised Sentiment Classification Method for Chinese Microblogs","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-with-expert-advice","title":"Active Learning with Expert Advice","date":"2013-09-26","arxiv_id":"1309.6875","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-bridges-viewing-active-learning-from","title":"Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens","date":"2013-09-26","arxiv_id":"1309.6830","repositories_listed":0,"syntology":null}],"record_sha256":"9d58512a46b7862b41a584eea3c676752e58daaff333eecb660b8e34ac1a5c31","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}