{"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/48","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":48,"pages_in_order":129,"rows_per_page":100,"rows":[4701,4800],"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/47","next":"/task/classification-1/papers/49","papers":[{"url":null,"slug":"document-author-classification-using-parsed","title":"Document Author Classification Using Parsed Language Structure","date":"2024-03-20","arxiv_id":"2403.13253","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecosense-energy-efficient-intelligent-sensing","title":"EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration","date":"2024-03-20","arxiv_id":"2403.14027","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-large-language-models-for","title":"Enhancing Traffic Incident Management with Large Language Models: A Hybrid Machine Learning Approach for Severity Classification","date":"2024-03-20","arxiv_id":"2403.13547","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-feature-communication-in-federated","title":"Leveraging feature communication in federated learning for remote sensing image classification","date":"2024-03-20","arxiv_id":"2403.13575","repositories_listed":0,"syntology":null},{"url":null,"slug":"loss-regularizing-robotic-terrain","title":"Loss Regularizing Robotic Terrain Classification","date":"2024-03-20","arxiv_id":"2403.13695","repositories_listed":0,"syntology":null},{"url":"/paper/a-hybrid-transformer-sequencer-approach-for","slug":"a-hybrid-transformer-sequencer-approach-for","title":"A Hybrid Transformer-Sequencer approach for Age and Gender classification from in-wild facial images","date":"2024-03-19","arxiv_id":"2403.12483","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-eatformer-a-vision-transformer-for","title":"Improved EATFormer: A Vision Transformer for Medical Image Classification","date":"2024-03-19","arxiv_id":"2403.13167","repositories_listed":0,"syntology":null},{"url":null,"slug":"finllama-financial-sentiment-classification","title":"FinLlama: Financial Sentiment Classification for Algorithmic Trading Applications","date":"2024-03-18","arxiv_id":"2403.12285","repositories_listed":0,"syntology":null},{"url":null,"slug":"fuzzy-rough-choquet-distances-for","title":"Fuzzy Rough Choquet Distances for Classification","date":"2024-03-18","arxiv_id":"2403.11843","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalizing-deep-learning-models-for-medical","title":"A Systematic Review of Generalization Research in Medical Image Classification","date":"2024-03-18","arxiv_id":"2403.12167","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-spatial-and-semantic-feature","title":"Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks","date":"2024-03-18","arxiv_id":"2403.12009","repositories_listed":0,"syntology":null},{"url":null,"slug":"molecular-classification-using","title":"Molecular Classification Using Hyperdimensional Graph Classification","date":"2024-03-18","arxiv_id":"2403.12307","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-modified-word-saliency-based-adversarial","title":"A Modified Word Saliency-Based Adversarial Attack on Text Classification Models","date":"2024-03-17","arxiv_id":"2403.11297","repositories_listed":0,"syntology":null},{"url":null,"slug":"cbr-boosting-adaptive-classification-by","title":"CBR - Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution","date":"2024-03-17","arxiv_id":"2403.11206","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-classification-for-intrusion","title":"Hierarchical Classification for Intrusion Detection System: Effective Design and Empirical Analysis","date":"2024-03-17","arxiv_id":"2403.13013","repositories_listed":0,"syntology":null},{"url":null,"slug":"fishnet-deep-neural-networks-for-low-cost","title":"FishNet: Deep Neural Networks for Low-Cost Fish Stock Estimation","date":"2024-03-16","arxiv_id":"2403.10916","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-study-on-machine-learning-1","title":"A comparative study on machine learning approaches for rock mass classification using drilling data","date":"2024-03-15","arxiv_id":"2403.10404","repositories_listed":0,"syntology":null},{"url":null,"slug":"frozen-feature-augmentation-for-few-shot","title":"Frozen Feature Augmentation for Few-Shot Image Classification","date":"2024-03-15","arxiv_id":"2403.10519","repositories_listed":0,"syntology":null},{"url":null,"slug":"linear-optimal-transport-subspaces-for-point","title":"Linear optimal transport subspaces for point set classification","date":"2024-03-15","arxiv_id":"2403.10015","repositories_listed":0,"syntology":null},{"url":null,"slug":"randomized-principal-component-analysis-for","title":"Randomized Principal Component Analysis for Hyperspectral Image Classification","date":"2024-03-14","arxiv_id":"2403.09117","repositories_listed":0,"syntology":null},{"url":null,"slug":"iterative-online-image-synthesis-via","title":"Iterative Online Image Synthesis via Diffusion Model for Imbalanced Classification","date":"2024-03-13","arxiv_id":"2403.08407","repositories_listed":0,"syntology":null},{"url":null,"slug":"pig-aggression-classification-using-cnn","title":"Pig aggression classification using CNN, Transformers and Recurrent Networks","date":"2024-03-13","arxiv_id":"2403.08528","repositories_listed":0,"syntology":null},{"url":null,"slug":"reduced-jeffries-matusita-distance-a-novel","title":"Reduced Jeffries-Matusita distance: A Novel Loss Function to Improve Generalization Performance of Deep Classification Models","date":"2024-03-13","arxiv_id":"2403.08408","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-flexible-cell-classification-for-ml","title":"A Flexible Cell Classification for ML Projects in Jupyter Notebooks","date":"2024-03-12","arxiv_id":"2403.07562","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-random-forest-ensemble-of","title":"A New Random Forest Ensemble of Intuitionistic Fuzzy Decision Trees","date":"2024-03-12","arxiv_id":"2403.07363","repositories_listed":0,"syntology":null},{"url":null,"slug":"rediscovering-bce-loss-for-uniform","title":"Rediscovering BCE Loss for Uniform Classification","date":"2024-03-12","arxiv_id":"2403.07289","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-time-series-classification-for","title":"Supervised Time Series Classification for Anomaly Detection in Subsea Engineering","date":"2024-03-12","arxiv_id":"2403.08013","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-machine-learning-dataset-of-bulldog","title":"A New Machine Learning Dataset of Bulldog Nostril Images for Stenosis Degree Classification","date":"2024-03-11","arxiv_id":"2403.07132","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-slice-classification-neural-network-for","title":"A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset","date":"2024-03-11","arxiv_id":"2403.07105","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-quantum-tensor-networks-for","title":"Application of Quantum Tensor Networks for Protein Classification","date":"2024-03-11","arxiv_id":"2403.06890","repositories_listed":0,"syntology":null},{"url":null,"slug":"heterogeneous-image-based-classification","title":"Heterogeneous Image-based Classification Using Distributional Data Analysis","date":"2024-03-11","arxiv_id":"2403.07126","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpreting-what-typical-fault-signals-look","title":"Interpreting What Typical Fault Signals Look Like via Prototype-matching","date":"2024-03-11","arxiv_id":"2403.07033","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-internal-representations-of-model","title":"Leveraging Internal Representations of Model for Magnetic Image Classification","date":"2024-03-11","arxiv_id":"2403.06797","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adversarial-active-learning-for-domain","title":"Domain Adversarial Active Learning for Domain Generalization Classification","date":"2024-03-10","arxiv_id":"2403.06174","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-classification-robustness-and-explanation","title":"Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape","date":"2024-03-09","arxiv_id":"2403.06013","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-classification-performance-via","title":"Enhancing Classification Performance via Reinforcement Learning for Feature Selection","date":"2024-03-09","arxiv_id":"2403.05979","repositories_listed":0,"syntology":null},{"url":null,"slug":"fault-classification-in-electrical","title":"Fault Classification in Electrical Distribution Systems using Grassmann Manifold","date":"2024-03-09","arxiv_id":"2403.05991","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-query-classification-in-e","title":"Hierarchical Query Classification in E-commerce Search","date":"2024-03-09","arxiv_id":"2403.06021","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-cam-interpretable-ai-in-image","title":"Feature CAM: Interpretable AI in Image Classification","date":"2024-03-08","arxiv_id":"2403.05658","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-expressive-and-generalizable-motion","title":"Learning Expressive And Generalizable Motion Features For Face Forgery Detection","date":"2024-03-08","arxiv_id":"2403.05172","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-speech-symptoms-classification-via","title":"Medical Speech Symptoms Classification via Disentangled Representation","date":"2024-03-08","arxiv_id":"2403.05000","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-self-supervised-learning-complexity","title":"Reducing self-supervised learning complexity improves weakly-supervised classification performance in computational pathology","date":"2024-03-07","arxiv_id":"2403.04558","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatiotemporal-pooling-on-appropriate","title":"Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification","date":"2024-03-07","arxiv_id":"2403.04353","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learned-compression-for-radio-frequency","title":"Deep-Learned Compression for Radio-Frequency Signal Classification","date":"2024-03-05","arxiv_id":"2403.03150","repositories_listed":0,"syntology":null},{"url":null,"slug":"ub-finenet-urban-building-fine-grained","title":"UB-FineNet: Urban Building Fine-grained Classification Network for Open-access Satellite Images","date":"2024-03-04","arxiv_id":"2403.02132","repositories_listed":0,"syntology":null},{"url":null,"slug":"limits-to-classification-performance-by","title":"Limits to classification performance by relating Kullback-Leibler divergence to Cohen's Kappa","date":"2024-03-03","arxiv_id":"2403.01571","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-field-classifiers-via-target-encoding","title":"Neural Field Classifiers via Target Encoding and Classification Loss","date":"2024-03-02","arxiv_id":"2403.01058","repositories_listed":0,"syntology":null},{"url":null,"slug":"learnability-gaps-of-strategic-classification","title":"Learnability Gaps of Strategic Classification","date":"2024-02-29","arxiv_id":"2402.19303","repositories_listed":0,"syntology":null},{"url":null,"slug":"teleclass-taxonomy-enrichment-and-llm","title":"TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision","date":"2024-02-29","arxiv_id":"2403.00165","repositories_listed":0,"syntology":null},{"url":null,"slug":"unraveling-adversarial-examples-against","title":"Unraveling Adversarial Examples against Speaker Identification -- Techniques for Attack Detection and Victim Model Classification","date":"2024-02-29","arxiv_id":"2402.19355","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-machine-learning-for-multi-label","title":"Automated Machine Learning for Multi-Label Classification","date":"2024-02-28","arxiv_id":"2402.18198","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotion-classification-in-low-and-moderate","title":"Emotion Classification in Low and Moderate Resource Languages","date":"2024-02-28","arxiv_id":"2402.18424","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-regularized-encoder-training-for","title":"Graph Regularized Encoder Training for Extreme Classification","date":"2024-02-28","arxiv_id":"2402.18434","repositories_listed":0,"syntology":null},{"url":null,"slug":"conformal-shield-a-novel-adversarial-attack","title":"Conformal Shield: A Novel Adversarial Attack Detection Framework for Automatic Modulation Classification","date":"2024-02-27","arxiv_id":"2402.17450","repositories_listed":0,"syntology":null},{"url":null,"slug":"fuzzy-classification-aggregation","title":"Fuzzy Classification Aggregation","date":"2024-02-27","arxiv_id":"2402.17620","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligent-known-and-novel-aircraft","title":"Intelligent Known and Novel Aircraft Recognition -- A Shift from Classification to Similarity Learning for Combat Identification","date":"2024-02-26","arxiv_id":"2402.16486","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-the-robustness-of-vision","title":"Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification","date":"2024-02-26","arxiv_id":"2402.16734","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-shot-graph-representation-learning-using","title":"Hyperdimensional Representation Learning for Node Classification and Link Prediction","date":"2024-02-26","arxiv_id":"2402.17073","repositories_listed":0,"syntology":null},{"url":null,"slug":"calibration-of-deep-learning-classification","title":"Calibration of Deep Learning Classification Models in fNIRS","date":"2024-02-23","arxiv_id":"2402.15266","repositories_listed":0,"syntology":null},{"url":null,"slug":"carbd-ko-a-contextually-annotated-review","title":"CARBD-Ko: A Contextually Annotated Review Benchmark Dataset for Aspect-Level Sentiment Classification in Korean","date":"2024-02-23","arxiv_id":"2402.15046","repositories_listed":0,"syntology":null},{"url":null,"slug":"retinotopic-mapping-enhances-the-robustness","title":"Foveated Retinotopy Improves Classification and Localization in CNNs","date":"2024-02-23","arxiv_id":"2402.15480","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparison-of-machine-learning-classification","title":"Comparison of Machine Learning Classification Algorithms and Application to the Framingham Heart Study","date":"2024-02-22","arxiv_id":"2402.15005","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-power-quality-event-classification","title":"Enhancing Power Quality Event Classification with AI Transformer Models","date":"2024-02-22","arxiv_id":"2402.14949","repositories_listed":0,"syntology":null},{"url":null,"slug":"balancing-spectral-temporal-and-spatial","title":"Balancing Spectral, Temporal and Spatial Information for EEG-based Alzheimer's Disease Classification","date":"2024-02-21","arxiv_id":"2402.13523","repositories_listed":0,"syntology":null},{"url":null,"slug":"effects-of-term-weighting-approach-with-and","title":"Effects of term weighting approach with and without stop words removing on Arabic text classification","date":"2024-02-21","arxiv_id":"2402.14867","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-classification-techniques-for","title":"Automation of Quantum Dot Measurement Analysis via Explainable Machine Learning","date":"2024-02-21","arxiv_id":"2402.13699","repositories_listed":0,"syntology":null},{"url":null,"slug":"buffgraph-enhancing-class-imbalanced-node","title":"BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes","date":"2024-02-20","arxiv_id":"2402.13114","repositories_listed":0,"syntology":null},{"url":null,"slug":"handling-ambiguity-in-emotion-from-out-of","title":"Handling Ambiguity in Emotion: From Out-of-Domain Detection to Distribution Estimation","date":"2024-02-20","arxiv_id":"2402.12862","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-neural-based-classification-with","title":"Improving Neural-based Classification with Logical Background Knowledge","date":"2024-02-20","arxiv_id":"2402.13019","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adversarial-approach-to-evaluating-the","title":"An Adversarial Approach to Evaluating the Robustness of Event Identification Models","date":"2024-02-19","arxiv_id":"2402.12338","repositories_listed":0,"syntology":null},{"url":null,"slug":"causal-equal-protection-as-algorithmic","title":"Causal Equal Protection as Algorithmic Fairness","date":"2024-02-19","arxiv_id":"2402.12062","repositories_listed":0,"syntology":null},{"url":null,"slug":"performance-of-using-mel-frequency-cepstrum","title":"Performance of using Mel-Frequency Cepstrum Based Features in Nonlinear Classifiers for Phonocardiography Recordings","date":"2024-02-19","arxiv_id":"2402.12540","repositories_listed":0,"syntology":null},{"url":null,"slug":"rock-classification-based-on-residual","title":"Rock Classification Based on Residual Networks","date":"2024-02-19","arxiv_id":"2402.11831","repositories_listed":0,"syntology":null},{"url":null,"slug":"thyroid-ultrasound-diagnosis-improvement-via","title":"Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training","date":"2024-02-18","arxiv_id":"2402.11497","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-class-temporal-logic-neural-networks","title":"Multi-class Temporal Logic Neural Networks","date":"2024-02-17","arxiv_id":"2402.12397","repositories_listed":0,"syntology":null},{"url":null,"slug":"ransomware-detection-using-stacked","title":"Ransomware detection using stacked autoencoder for feature selection","date":"2024-02-17","arxiv_id":"2402.11342","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-bit-quantization-and-sparsification-for","title":"One-Bit Quantization and Sparsification for Multiclass Linear Classification with Strong Regularization","date":"2024-02-16","arxiv_id":"2402.10474","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-diffusion-models","title":"Classification Diffusion Models: Revitalizing Density Ratio Estimation","date":"2024-02-15","arxiv_id":"2402.10095","repositories_listed":0,"syntology":null},{"url":null,"slug":"hand-shape-and-gesture-recognition-using","title":"Hand Shape and Gesture Recognition using Multiscale Template Matching, Background Subtraction and Binary Image Analysis","date":"2024-02-15","arxiv_id":"2402.09663","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiview-contrastive-learning-for","title":"Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces","date":"2024-02-15","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-machine-learning-for-signal","title":"Utilizing Machine Learning for Signal Classification and Noise Reduction in Amateur Radio","date":"2024-02-15","arxiv_id":"2402.17771","repositories_listed":0,"syntology":null},{"url":null,"slug":"distribution-free-rates-in-neyman-pearson","title":"Distribution-Free Rates in Neyman-Pearson Classification","date":"2024-02-14","arxiv_id":"2402.09560","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-based-bone-quality-classification","title":"Learning-based Bone Quality Classification Method for Spinal Metastasis","date":"2024-02-14","arxiv_id":"2402.08910","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-low-rank-feature-for-thorax-disease","title":"Learning Low-Rank Feature for Thorax Disease Classification","date":"2024-02-14","arxiv_id":"2404.18933","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-rank-graph-contrastive-learning-for-node","title":"Low-Rank Graph Contrastive Learning for Node Classification","date":"2024-02-14","arxiv_id":"2402.09600","repositories_listed":0,"syntology":null},{"url":null,"slug":"only-my-model-on-my-data-a-privacy-preserving","title":"Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models","date":"2024-02-14","arxiv_id":"2402.09316","repositories_listed":0,"syntology":null},{"url":null,"slug":"synergistic-eigenanalysis-of-covariance-and","title":"Synergistic eigenanalysis of covariance and Hessian matrices for enhanced binary classification","date":"2024-02-14","arxiv_id":"2402.09281","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-strategic-classification","title":"Bayesian Strategic Classification","date":"2024-02-13","arxiv_id":"2402.08758","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-structured-prediction-with-fenchel","title":"Online Structured Prediction with Fenchel--Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss","date":"2024-02-13","arxiv_id":"2402.08180","repositories_listed":0,"syntology":null},{"url":null,"slug":"bandit-feedback-online-multiclass","title":"Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs","date":"2024-02-12","arxiv_id":"2402.07453","repositories_listed":0,"syntology":null},{"url":null,"slug":"message-detouring-a-simple-yet-effective","title":"Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning","date":"2024-02-12","arxiv_id":"2402.08085","repositories_listed":0,"syntology":null},{"url":null,"slug":"pushing-the-limit-of-llm-capacity-for-text","title":"Pushing The Limit of LLM Capacity for Text Classification","date":"2024-02-12","arxiv_id":"2402.07470","repositories_listed":0,"syntology":null},{"url":null,"slug":"for-better-or-for-worse-learning-minimum","title":"For Better or For Worse? Learning Minimum Variance Features With Label Augmentation","date":"2024-02-10","arxiv_id":"2402.06855","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-enhancing-autoencoder-for-occluded","title":"Latent Enhancing AutoEncoder for Occluded Image Classification","date":"2024-02-10","arxiv_id":"2402.06936","repositories_listed":0,"syntology":null},{"url":null,"slug":"flexible-infinite-width-graph-convolutional","title":"Flexible infinite-width graph convolutional networks and the importance of representation learning","date":"2024-02-09","arxiv_id":"2402.06525","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-computational-job-market","title":"Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postings","date":"2024-02-08","arxiv_id":"2402.05617","repositories_listed":0,"syntology":null},{"url":null,"slug":"hypergraph-node-classification-with-graph","title":"Training-Free Message Passing for Learning on Hypergraphs","date":"2024-02-08","arxiv_id":"2402.05569","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixture-density-networks-for-classification","title":"Mixture Density Networks for Classification with an Application to Product Bundling","date":"2024-02-08","arxiv_id":"2402.05428","repositories_listed":0,"syntology":null},{"url":null,"slug":"segmentation-free-connectionist-temporal","title":"Segmentation-free Connectionist Temporal Classification loss based OCR Model for Text Captcha Classification","date":"2024-02-08","arxiv_id":"2402.05417","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-shape-and-contour-features-to","title":"Combining shape and contour features to improve tool wear monitoring in milling processes","date":"2024-02-07","arxiv_id":"2402.05978","repositories_listed":0,"syntology":null}],"record_sha256":"58b8193f0b969f761dfde085e2f2f16ff09fa8b2c2a05ed1315e9213e292ca1e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}