{"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/classification-1/papers/120","list_of":"/task/classification-1","task":"Classification","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":120,"pages_in_order":129,"rows_per_page":100,"rows":[11901,12000],"of":12815,"counts":{"archive_papers_tagged":12815,"with_a_code_link":3778,"where_syntology_ran_a_sample":582,"not_listed_spam_title":0,"listed":12815,"listed_where_code_ran":582,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":457,"every_run_a_failure_of_syntologys_instrument":125,"listed_with_a_run_with_no_instrument_failure":457,"listed_every_run_a_failure_of_syntologys_instrument":125,"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/classification-1","prev":"/task/classification-1/papers/119","next":"/task/classification-1/papers/121","papers":[{"url":null,"slug":"a-taxonomic-classification-of-wordnet","title":"A Taxonomic Classification of WordNet Polysemy Types","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"folktale-similarity-based-on-ontological","title":"Folktale similarity based on ontological abstraction","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/improving-question-classification-by-feature","slug":"improving-question-classification-by-feature","title":"Improving Question Classification by Feature Extraction and Selection","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-a-wordnet-based-classification-of","title":"Towards a WordNet based Classification of Actors in Folktales","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-satirical-articles-using-common","title":"Understanding Satirical Articles Using Common-Sense","date":"2016-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-semi-supervised-least-squares","title":"Robust Semi-supervised Least Squares Classification by Implicit Constraints","date":"2015-12-27","arxiv_id":"1512.08240","repositories_listed":0,"syntology":null},{"url":null,"slug":"part-stacked-cnn-for-fine-grained-visual","title":"Part-Stacked CNN for Fine-Grained Visual Categorization","date":"2015-12-26","arxiv_id":"1512.08086","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-utility-of-abstaining-in-binary","title":"The Utility of Abstaining in Binary Classification","date":"2015-12-26","arxiv_id":"1512.08133","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multiresolution-clinical-decision-support","title":"A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours","date":"2015-12-25","arxiv_id":"1512.08051","repositories_listed":0,"syntology":null},{"url":null,"slug":"texture-measures-combination-for-improved","title":"Texture measures combination for improved meningioma classification of histopathological images","date":"2015-12-25","arxiv_id":"1512.08049","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-architecture-exploration-for","title":"Convolutional Architecture Exploration for Action Recognition and Image Classification","date":"2015-12-23","arxiv_id":"1512.07502","repositories_listed":0,"syntology":null},{"url":null,"slug":"cost-based-feature-transfer-for-vehicle","title":"Cost-based Feature Transfer for Vehicle Occupant Classification","date":"2015-12-22","arxiv_id":"1512.07080","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-selection-for-classification-under","title":"Feature Selection for Classification under Anonymity Constraint","date":"2015-12-22","arxiv_id":"1512.07158","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-classification-latent-user-interests","title":"Beyond Classification: Latent User Interests Profiling from Visual Contents Analysis","date":"2015-12-21","arxiv_id":"1512.06785","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-surface-material","title":"Deep Learning for Surface Material Classification Using Haptic And Visual Information","date":"2015-12-21","arxiv_id":"1512.06658","repositories_listed":0,"syntology":null},{"url":null,"slug":"kernel-principal-component-analysis-network","title":"Kernel principal component analysis network for image classification","date":"2015-12-20","arxiv_id":"1512.06337","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiclass-classification-of-cervical-cancer","title":"Multiclass Classification of Cervical Cancer Tissues by Hidden Markov Model","date":"2015-12-18","arxiv_id":"1512.06014","repositories_listed":0,"syntology":null},{"url":null,"slug":"spherical-distance-metrics-applied-to-protein","title":"Spherical Distance Metrics Applied to Protein Structure Classification","date":"2015-12-18","arxiv_id":"1602.08079","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-of-weak-multi-view-signals-by","title":"Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers","date":"2015-12-17","arxiv_id":"1512.05610","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-evaluation-of-cultural-scale-claims","title":"Towards Evaluation of Cultural-scale Claims in Light of Topic Model Sampling Effects","date":"2015-12-15","arxiv_id":"1512.05004","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-incident-classification-for-big","title":"Automatic Incident Classification for Big Traffic Data by Adaptive Boosting SVM","date":"2015-12-14","arxiv_id":"1512.04392","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-enriched-visual-vocabulary","title":"Semantic-enriched Visual Vocabulary Construction in a Weakly Supervised Context","date":"2015-12-14","arxiv_id":"1512.04605","repositories_listed":0,"syntology":null},{"url":null,"slug":"stack-exchange-tagger","title":"Stack Exchange Tagger","date":"2015-12-13","arxiv_id":"1512.04092","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-deep-feature-learning-and","title":"Efficient Deep Feature Learning and Extraction via StochasticNets","date":"2015-12-11","arxiv_id":"1512.03844","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-grained-image-classification-by","title":"Fine-grained Image Classification by Exploring Bipartite-Graph Labels","date":"2015-12-08","arxiv_id":"1512.02665","repositories_listed":0,"syntology":null},{"url":null,"slug":"prototypical-priors-from-improving","title":"Prototypical Priors: From Improving Classification to Zero-Shot Learning","date":"2015-12-03","arxiv_id":"1512.01192","repositories_listed":0,"syntology":null},{"url":null,"slug":"centroid-based-binary-tree-structured-svm-for","title":"Centroid Based Binary Tree Structured SVM for Multi Classification","date":"2015-12-02","arxiv_id":"1512.00659","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-classifiers-fisher-vectors-and-deep","title":"Analyzing Classifiers: Fisher Vectors and Deep Neural Networks","date":"2015-12-01","arxiv_id":"1512.00172","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-analysis-of-bangla-poetry-for","title":"Automated Analysis of Bangla Poetry for Classification and Poet Identification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"consistent-multilabel-classification","title":"Consistent Multilabel Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"contractive-rectifier-networks-for-nonlinear","title":"Contractive Rectifier Networks for Nonlinear Maximum Margin Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dependency-extraction-for-knowledge-based","title":"Dependency Extraction for Knowledge-based Domain Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-classification-rates-for-high","title":"Fast Classification Rates for High-dimensional Gaussian Generative Models","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-ferns-ensembles-by-sparsifying-and","title":"Improving Ferns Ensembles by Sparsifying and Quantising Posterior Probabilities","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mood-classification-of-hindi-songs-based-on","title":"Mood Classification of Hindi Songs based on Lyrics","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-optimality-of-classifier-chain-for","title":"On the Optimality of Classifier Chain for Multi-label Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"online-adspace-posts-category-classification","title":"Online Adspace Posts' Category Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"predtron-a-family-of-online-algorithms-for","title":"Predtron: A Family of Online Algorithms for General Prediction Problems","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-appearance-models-for","title":"Probabilistic Appearance Models for Segmentation and Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-organizing-maps-for-classification-of-a","title":"Self-Organizing Maps for Classification of a Multi-Labeled Corpus","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-zero-shot-classification-with","title":"Semi-Supervised Zero-Shot Classification With Label Representation Learning","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-foreground-detection-and","title":"Simultaneous Foreground Detection and Classification With Hybrid Features","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-local-embeddings-for-extreme-multi","title":"Sparse Local Embeddings for Extreme Multi-label Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"task-driven-feature-pooling-for-image","title":"Task-Driven Feature Pooling for Image Classification","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"aspect-based-opinion-summarization-with","title":"Aspect-based Opinion Summarization with Convolutional Neural Networks","date":"2015-11-30","arxiv_id":"1511.09128","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-grained-classification-via-mixture-of","title":"Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks","date":"2015-11-30","arxiv_id":"1511.09209","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-coral-classification-using-deep","title":"Sparse Coral Classification Using Deep Convolutional Neural Networks","date":"2015-11-29","arxiv_id":"1511.09067","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparseness-helps-sparsity-augmented","title":"Sparseness helps: Sparsity Augmented Collaborative Representation for Classification","date":"2015-11-29","arxiv_id":"1511.08956","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-classification-of-e-commerce","title":"Hierarchical classification of e-commerce related social media","date":"2015-11-26","arxiv_id":"1511.08299","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-correlation-between-labels-to","title":"Exploring Correlation between Labels to improve Multi-Label Classification","date":"2015-11-25","arxiv_id":"1511.07953","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-deep-feature-extraction-for","title":"Unsupervised Deep Feature Extraction for Remote Sensing Image Classification","date":"2015-11-25","arxiv_id":"1511.08131","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-two-level-boolean-rule-learning","title":"Interpretable Two-level Boolean Rule Learning for Classification","date":"2015-11-23","arxiv_id":"1511.07361","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-linear-models-applied-to-power-quality","title":"Sparse Linear Models applied to Power Quality Disturbance Classification","date":"2015-11-23","arxiv_id":"1511.07281","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-sentential-utterances-in-dialogue","title":"Non-Sentential Utterances in Dialogue: Experiments in Classification and Interpretation","date":"2015-11-22","arxiv_id":"1511.06995","repositories_listed":0,"syntology":null},{"url":null,"slug":"l1-logistic-regression-as-a-feature-selection","title":"L1 logistic regression as a feature selection step for training stable classification trees for the prediction of severity criteria in imported malaria","date":"2015-11-20","arxiv_id":"1511.06663","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-cnns-with-low-rank-filters-for","title":"Training CNNs with Low-Rank Filters for Efficient Image Classification","date":"2015-11-20","arxiv_id":"1511.06744","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-much-data-is-needed-to-train-a-medical","title":"How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?","date":"2015-11-19","arxiv_id":"1511.06348","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-sparse-representation-learning-and","title":"Multimodal sparse representation learning and applications","date":"2015-11-19","arxiv_id":"1511.06238","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-classification-by-pre-conditioned","title":"Robust Classification by Pre-conditioned LASSO and Transductive Diffusion Component Analysis","date":"2015-11-19","arxiv_id":"1511.06340","repositories_listed":0,"syntology":null},{"url":"/paper/pronet-learning-to-propose-object-specific","slug":"pronet-learning-to-propose-object-specific","title":"ProNet: Learning to Propose Object-specific Boxes for Cascaded Neural Networks","date":"2015-11-12","arxiv_id":"1511.03776","repositories_listed":0,"syntology":null},{"url":null,"slug":"datagrinder-fast-accurate-fully-non","title":"DataGrinder: Fast, Accurate, Fully non-Parametric Classification Approach Using 2D Convex Hulls","date":"2015-11-11","arxiv_id":"1511.03576","repositories_listed":0,"syntology":null},{"url":null,"slug":"facial-expression-detection-using-patch-based","title":"Facial Expression Detection using Patch-based Eigen-face Isomap Networks","date":"2015-11-11","arxiv_id":"1511.03363","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hierarchical-spectral-method-for-extreme","title":"A Hierarchical Spectral Method for Extreme Classification","date":"2015-11-10","arxiv_id":"1511.03260","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-expectation-propagation-for-large","title":"Stochastic Expectation Propagation for Large Scale Gaussian Process Classification","date":"2015-11-10","arxiv_id":"1511.03249","repositories_listed":0,"syntology":null},{"url":null,"slug":"performance-analysis-of-multiclass-support","title":"Performance Analysis of Multiclass Support Vector Machine Classification for Diagnosis of Coronary Heart Diseases","date":"2015-11-07","arxiv_id":"1511.02352","repositories_listed":0,"syntology":null},{"url":null,"slug":"review-level-sentiment-classification-with","title":"Review-Level Sentiment Classification with Sentence-Level Polarity Correction","date":"2015-11-07","arxiv_id":"1511.02385","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-classification-based-on-support-vector","title":"Image classification based on support vector machine and the fusion of complementary features","date":"2015-11-05","arxiv_id":"1511.01706","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-an-efficient-multi-class","title":"Toward an Efficient Multi-class Classification in an Open Universe","date":"2015-11-02","arxiv_id":"1511.00725","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-based-diversity-optimization-for","title":"Feature-Based Diversity Optimization for Problem Instance Classification","date":"2015-10-29","arxiv_id":"1510.08568","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-semi-supervised-classification-for","title":"Robust Semi-Supervised Classification for Multi-Relational Graphs","date":"2015-10-19","arxiv_id":"1510.06024","repositories_listed":0,"syntology":null},{"url":null,"slug":"normalization-of-relative-and-incomplete","title":"Normalization of Relative and Incomplete Temporal Expressions in Clinical Narratives","date":"2015-10-16","arxiv_id":"1510.04972","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-multiclass-segmentation-using","title":"Interactive multiclass segmentation using superpixel classification","date":"2015-10-12","arxiv_id":"1510.03199","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-knowledge-gradient-with-logistic-belief","title":"The Knowledge Gradient with Logistic Belief Models for Binary Classification","date":"2015-10-08","arxiv_id":"1510.02354","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-estimation-of-class-prior","title":"Improved Estimation of Class Prior Probabilities through Unlabeled Data","date":"2015-10-06","arxiv_id":"1510.01422","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-daily-activities-from-egocentric","title":"Predicting Daily Activities From Egocentric Images Using Deep Learning","date":"2015-10-06","arxiv_id":"1510.01576","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-in-unlabeled-networks-an-active","title":"Learning in Unlabeled Networks - An Active Learning and Inference Approach","date":"2015-10-05","arxiv_id":"1510.01270","repositories_listed":0,"syntology":null},{"url":null,"slug":"within-brain-classification-for-brain-tumor","title":"Within-Brain Classification for Brain Tumor Segmentation","date":"2015-10-05","arxiv_id":"1510.01344","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-approach-to-document-classification","title":"A Novel Approach to Document Classification using WordNet","date":"2015-10-04","arxiv_id":"1510.02755","repositories_listed":0,"syntology":null},{"url":null,"slug":"client-profiling-for-an-anti-money-laundering","title":"Client Profiling for an Anti-Money Laundering System","date":"2015-10-03","arxiv_id":"1510.00878","repositories_listed":0,"syntology":null},{"url":"/paper/whoi-plankton-a-large-scale-fine-grained","slug":"whoi-plankton-a-large-scale-fine-grained","title":"WHOI-Plankton- A Large Scale Fine Grained Visual Recognition Benchmark Dataset for Plankton Classification","date":"2015-10-02","arxiv_id":"1510.00745","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-filter-feature-selection-for","title":"A Comprehensive Filter Feature Selection for Improving Document Classification","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"annotation-and-classification-of-french","title":"Annotation and Classification of French Feedback Communicative Functions","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-classification-of-spoken-languages","title":"Automatic Classification of Spoken Languages using Diverse Acoustic Features","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/bidirectional-long-short-term-memory-networks","slug":"bidirectional-long-short-term-memory-networks","title":"Bidirectional Long Short-Term Memory Networks for Relation Classification","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"thai-stock-news-sentiment-classification","title":"Thai Stock News Sentiment Classification using Wordpair Features","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-haar-scattering-networks","title":"Deep Haar Scattering Networks","date":"2015-09-30","arxiv_id":"1509.09187","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-deep-learning-for-energy","title":"Conditional Deep Learning for Energy-Efficient and Enhanced Pattern Recognition","date":"2015-09-29","arxiv_id":"1509.08971","repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-learning-of-the-prototype-set","title":"Discriminative Learning of the Prototype Set for Nearest Neighbor Classification","date":"2015-09-27","arxiv_id":"1509.08102","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-selection-for-classification-of","title":"Feature Selection for classification of hyperspectral data by minimizing a tight bound on the VC dimension","date":"2015-09-27","arxiv_id":"1509.08112","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-asymptotic-analysis-of-ell_1-norm-support","title":"Non-asymptotic Analysis of $\\ell_1$-norm Support Vector Machines","date":"2015-09-27","arxiv_id":"1509.08083","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatially-encoding-temporal-correlations-to","title":"Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks","date":"2015-09-24","arxiv_id":"1509.07481","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-error-in-multiclass","title":"Classification error in multiclass discrimination from Markov data","date":"2015-09-22","arxiv_id":"1509.06673","repositories_listed":0,"syntology":null},{"url":null,"slug":"understand-scene-categories-by-objects-a","title":"Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks","date":"2015-09-22","arxiv_id":"1509.06470","repositories_listed":0,"syntology":null},{"url":null,"slug":"fusing-multi-stream-deep-networks-for-video","title":"Fusing Multi-Stream Deep Networks for Video Classification","date":"2015-09-21","arxiv_id":"1509.06086","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-text-classification-a-naive-solution","title":"Early text classification: a Naive solution","date":"2015-09-20","arxiv_id":"1509.06053","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fuzzy-mlp-approach-for-non-linear-pattern","title":"A Fuzzy MLP Approach for Non-linear Pattern Classification","date":"2015-09-19","arxiv_id":"1601.03481","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-fishers-linear-discriminant-analysis","title":"Sparse Fisher's Linear Discriminant Analysis for Partially Labeled Data","date":"2015-09-17","arxiv_id":"1509.05438","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-image-classification-via-svm-using","title":"Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data","date":"2015-09-15","arxiv_id":"1509.04619","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-binary-classification-with-single-layer","title":"On Binary Classification with Single-Layer Convolutional Neural Networks","date":"2015-09-13","arxiv_id":"1509.03891","repositories_listed":0,"syntology":null},{"url":null,"slug":"verbs-taking-clausal-and-non-finite-arguments","title":"Verbs Taking Clausal and Non-Finite Arguments as Signals of Modality - Revisiting the Issue of Meaning Grounded in Syntax","date":"2015-09-11","arxiv_id":"1509.03488","repositories_listed":0,"syntology":null}],"record_sha256":"0ebcd6d4b26e9ac5fa8f0ff7091ff46cc4995df1e2c0cd14457a68e83a754c10","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}