{"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/domain-adaptation/papers/57","list_of":"/task/domain-adaptation","task":"Domain Adaptation","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":57,"pages_in_order":65,"rows_per_page":100,"rows":[5601,5700],"of":6439,"counts":{"archive_papers_tagged":6439,"with_a_code_link":2400,"where_syntology_ran_a_sample":517,"not_listed_spam_title":0,"listed":6439,"listed_where_code_ran":517,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":442,"every_run_a_failure_of_syntologys_instrument":75,"listed_with_a_run_with_no_instrument_failure":442,"listed_every_run_a_failure_of_syntologys_instrument":75,"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/domain-adaptation","prev":"/task/domain-adaptation/papers/56","next":"/task/domain-adaptation/papers/58","papers":[{"url":null,"slug":"a-general-approach-to-domain-adaptation-with","title":"A General Approach to Domain Adaptation with Applications in Astronomy","date":"2018-12-20","arxiv_id":"1812.08839","repositories_listed":0,"syntology":null},{"url":null,"slug":"patent-retrieval-a-literature-review","title":"Patent Retrieval: A Literature Review","date":"2018-12-20","arxiv_id":"1701.00324","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-database-micro-expression-recognition-a","title":"Cross-Database Micro-Expression Recognition: A Benchmark","date":"2018-12-19","arxiv_id":"1812.07742","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-for-reinforcement-learning","title":"Domain Adaptation for Reinforcement Learning on the Atari","date":"2018-12-18","arxiv_id":"1812.07452","repositories_listed":0,"syntology":null},{"url":null,"slug":"sim-to-real-via-sim-to-sim-data-efficient","title":"Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks","date":"2018-12-18","arxiv_id":"1812.07252","repositories_listed":0,"syntology":null},{"url":null,"slug":"twins-two-weighted-inconsistency-reduced","title":"TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain Adaptation","date":"2018-12-18","arxiv_id":"1812.07405","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-on-graphs-by-learning-graph","title":"Domain Adaptation on Graphs by Learning Graph Topologies: Theoretical Analysis and an Algorithm","date":"2018-12-17","arxiv_id":"1812.06944","repositories_listed":0,"syntology":null},{"url":null,"slug":"pac-learning-guarantees-under-covariate-shift","title":"PAC Learning Guarantees Under Covariate Shift","date":"2018-12-16","arxiv_id":"1812.06393","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-parametric-top-view-representation-of","title":"A Parametric Top-View Representation of Complex Road Scenes","date":"2018-12-14","arxiv_id":"1812.06152","repositories_listed":0,"syntology":null},{"url":null,"slug":"attentional-road-safety-networks","title":"Attentional Road Safety Networks","date":"2018-12-12","arxiv_id":"1812.04860","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-domain-adaptation-unseen-domain","title":"Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models","date":"2018-12-09","arxiv_id":"1812.03407","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-health-risk-model-based-on-intraday","title":"A novel health risk model based on intraday physical activity time series collected by smartphones","date":"2018-12-06","arxiv_id":"1812.02522","repositories_listed":0,"syntology":null},{"url":"/paper/disjoint-label-space-transfer-learning-with","slug":"disjoint-label-space-transfer-learning-with","title":"Disjoint Label Space Transfer Learning with Common Factorised Space","date":"2018-12-06","arxiv_id":"1812.02605","repositories_listed":0,"syntology":null},{"url":null,"slug":"forensictransfer-weakly-supervised-domain","title":"ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detection","date":"2018-12-06","arxiv_id":"1812.02510","repositories_listed":0,"syntology":null},{"url":null,"slug":"omnia-faster-r-cnn-detection-in-the-wild","title":"OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation","date":"2018-12-06","arxiv_id":"1812.02611","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-continuous-domain-adaptation-for","title":"Towards Continuous Domain adaptation for Healthcare","date":"2018-12-04","arxiv_id":"1812.01281","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferable-natural-language-interface-to","title":"Transferable Natural Language Interface to Structured Queries aided by Adversarial Generation","date":"2018-12-04","arxiv_id":"1812.01245","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-alignment-with-triplets","title":"Domain Alignment with Triplets","date":"2018-12-03","arxiv_id":"1812.00893","repositories_listed":0,"syntology":null},{"url":null,"slug":"splat-semantic-pixel-level-adaptation","title":"SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection","date":"2018-12-03","arxiv_id":"1812.00929","repositories_listed":0,"syntology":null},{"url":null,"slug":"vadra-visual-adversarial-domain-randomization","title":"Adversarial Domain Randomization","date":"2018-12-03","arxiv_id":"1812.00491","repositories_listed":0,"syntology":null},{"url":null,"slug":"eco-egocentric-cognitive-mapping","title":"ECO: Egocentric Cognitive Mapping","date":"2018-12-02","arxiv_id":"1812.00312","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-using-1","title":"Unsupervised Domain Adaptation using Generative Models and Self-ensembling","date":"2018-12-02","arxiv_id":"1812.00479","repositories_listed":0,"syntology":null},{"url":"/paper/adversarial-multiple-source-domain-adaptation","slug":"adversarial-multiple-source-domain-adaptation","title":"Adversarial Multiple Source Domain Adaptation","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-for-sentiment-analysis-1","title":"Domain Adaptation for Sentiment Analysis using Keywords in the Target Domain as the Learning Weight","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-using-a-combination-of","title":"Domain Adaptation Using a Combination of Multiple Embeddings for Sentiment Analysis","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"effectiveness-of-domain-adaptation-in","title":"Effectiveness of Domain Adaptation in Japanese Predicate-Argument Structure Analysis","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"osaka-university-mt-systems-for-wat-2018","title":"Osaka University MT Systems for WAT 2018: Rewarding, Preordering, and Domain Adaptation","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-epsilon-gamma-tau-similarity","title":"Revisiting (\\epsilon, \\gamma, \\tau)-similarity learning for domain adaptation","date":"2018-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-invariant-adversarial-learning-for","title":"Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption","date":"2018-11-30","arxiv_id":"1811.12751","repositories_listed":0,"syntology":null},{"url":null,"slug":"face-detection-in-the-operating-room","title":"Face Detection in the Operating Room: Comparison of State-of-the-art Methods and a Self-supervised Approach","date":"2018-11-29","arxiv_id":"1811.12296","repositories_listed":0,"syntology":null},{"url":null,"slug":"identity-preserving-generative-adversarial","title":"Identity Preserving Generative Adversarial Network for Cross-Domain Person Re-identification","date":"2018-11-28","arxiv_id":"1811.11510","repositories_listed":0,"syntology":null},{"url":null,"slug":"part-level-car-parsing-and-reconstruction","title":"Part-level Car Parsing and Reconstruction from Single Street View","date":"2018-11-27","arxiv_id":"1811.10837","repositories_listed":0,"syntology":null},{"url":null,"slug":"gantruth-an-unpaired-image-to-image","title":"GANtruth - an unpaired image-to-image translation method for driving scenarios","date":"2018-11-26","arxiv_id":"1812.01710","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-against-the-channel-effect-in","title":"Robustness against the channel effect in pathological voice detection","date":"2018-11-26","arxiv_id":"1811.10376","repositories_listed":0,"syntology":null},{"url":null,"slug":"similarity-preserving-image-image-domain","title":"Similarity-preserving Image-image Domain Adaptation for Person Re-identification","date":"2018-11-26","arxiv_id":"1811.10551","repositories_listed":0,"syntology":null},{"url":null,"slug":"population-aware-hierarchical-bayesian-domain","title":"Population-aware Hierarchical Bayesian Domain Adaptation","date":"2018-11-21","arxiv_id":"1811.08579","repositories_listed":0,"syntology":null},{"url":"/paper/progressive-feature-alignment-for","slug":"progressive-feature-alignment-for","title":"Progressive Feature Alignment for Unsupervised Domain Adaptation","date":"2018-11-21","arxiv_id":"1811.08585","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-discriminative-learning-for-unsupervised","title":"Deep Discriminative Learning for Unsupervised Domain Adaptation","date":"2018-11-17","arxiv_id":"1811.07134","repositories_listed":0,"syntology":null},{"url":"/paper/domain-adaptive-transfer-learning-with","slug":"domain-adaptive-transfer-learning-with","title":"Domain Adaptive Transfer Learning with Specialist Models","date":"2018-11-16","arxiv_id":"1811.07056","repositories_listed":0,"syntology":null},{"url":null,"slug":"implementing-a-portable-clinical-nlp-system","title":"Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective","date":"2018-11-15","arxiv_id":"1811.06179","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-generality-and-knowledge-transferability","title":"On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering","date":"2018-11-15","arxiv_id":"1811.06596","repositories_listed":0,"syntology":null},{"url":null,"slug":"theoretical-perspective-of-deep-domain","title":"On Deep Domain Adaptation: Some Theoretical Understandings","date":"2018-11-15","arxiv_id":"1811.06199","repositories_listed":0,"syntology":null},{"url":null,"slug":"co-regularized-alignment-for-unsupervised","title":"Co-regularized Alignment for Unsupervised Domain Adaptation","date":"2018-11-13","arxiv_id":"1811.05443","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-dimensionality-reduction-using","title":"Interactive dimensionality reduction using similarity projections","date":"2018-11-13","arxiv_id":"1811.05531","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-local-feature-patterns-for","title":"Exploiting Local Feature Patterns for Unsupervised Domain Adaptation","date":"2018-11-12","arxiv_id":"1811.05042","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-subspace-alignment-improves-domain","title":"Multiple Subspace Alignment Improves Domain Adaptation","date":"2018-11-11","arxiv_id":"1811.04491","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-semantic-segmentation-with-a","title":"Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels","date":"2018-11-08","arxiv_id":"1811.03542","repositories_listed":0,"syntology":null},{"url":null,"slug":"compact-personalized-models-for-neural","title":"Compact Personalized Models for Neural Machine Translation","date":"2018-11-05","arxiv_id":"1811.01990","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaption-of-bioasq-question-answering","title":"An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans.","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"transferable-positivenegative-speech-emotion","title":"Transferable Positive/Negative Speech Emotion Recognition via Class-wise Adversarial Domain Adaptation","date":"2018-10-30","arxiv_id":"1810.12782","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-answers-from-the-word-of-god-domain","title":"Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering","date":"2018-10-26","arxiv_id":"1810.12118","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-multi-target-domain-adaptation","title":"Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach","date":"2018-10-26","arxiv_id":"1810.11547","repositories_listed":0,"syntology":null},{"url":null,"slug":"tackling-sequence-to-sequence-mapping","title":"Tackling Sequence to Sequence Mapping Problems with Neural Networks","date":"2018-10-25","arxiv_id":"1810.10802","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-domain-adaptation-by-augmented-cyclic","title":"Robust Domain Adaptation By Augmented Cyclic Adversarial Learning","date":"2018-10-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dased-a-multi-domain-dataset-for-sound-event","title":"DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation","date":"2018-10-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-learning","title":"Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach","date":"2018-10-18","arxiv_id":"1810.07926","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-textual-and-speech-information-in","title":"Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation","date":"2018-10-17","arxiv_id":"1810.07455","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-semantics-in-adversarial-training","title":"Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation","date":"2018-10-13","arxiv_id":"1810.05852","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-domain-adaptation-framework-for","title":"A Novel Domain Adaptation Framework for Medical Image Segmentation","date":"2018-10-11","arxiv_id":"1810.05732","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-confusion-with-self-ensembling-for","title":"Domain Confusion with Self Ensembling for Unsupervised Adaptation","date":"2018-10-10","arxiv_id":"1810.04472","repositories_listed":0,"syntology":null},{"url":null,"slug":"seeing-beyond-appearance-mapping-real-images","title":"Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition","date":"2018-10-09","arxiv_id":"1810.04158","repositories_listed":0,"syntology":null},{"url":null,"slug":"spigan-privileged-adversarial-learning-from","title":"SPIGAN: Privileged Adversarial Learning from Simulation","date":"2018-10-09","arxiv_id":"1810.03756","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferring-physical-motion-between-domains","title":"Transferring Physical Motion Between Domains for Neural Inertial Tracking","date":"2018-10-04","arxiv_id":"1810.02076","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generalized-neyman-pearson-criterion-for","title":"A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation","date":"2018-10-03","arxiv_id":"1810.01545","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-approach-to-build-an-automatic-sentiment","title":"Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning","date":"2018-10-03","arxiv_id":"1810.01912","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-unsupervised-system-for-parallel-corpus","title":"An Unsupervised System for Parallel Corpus Filtering","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-detection-of-abusive-language","title":"Cross-Domain Detection of Abusive Language Online","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-diabetes-risk-from-social-media","title":"Detecting Diabetes Risk from Social Media Activity","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-named-entity-recognition-as-an","title":"Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hunter-nmt-system-for-wmt18-biomedical","title":"Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"lmu-munichas-neural-machine-translation","title":"LMU Munich's Neural Machine Translation Systems at WMT 2018","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-temporality-of-human-intentions-by","title":"Modeling Temporality of Human Intentions by Domain Adaptation","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"syntax-based-transfer-learning-for-the-task","title":"Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/transferring-from-formal-newswire-domain-with","slug":"transferring-from-formal-newswire-domain-with","title":"Transferring from Formal Newswire Domain with Hypernet for Twitter POS Tagging","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"translation-of-biomedical-documents-with","title":"Translation of Biomedical Documents with Focus on Spanish-English","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pixel-and-feature-level-based-domain-adaption","title":"Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving","date":"2018-09-30","arxiv_id":"1810.00345","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-domain-adaptation-for-stable","title":"Adversarial Domain Adaptation for Stable Brain-Machine Interfaces","date":"2018-09-28","arxiv_id":"1810.00045","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-monitoring-of-social-media-and","title":"Real Time Monitoring of Social Media and Digital Press","date":"2018-09-28","arxiv_id":"1810.00647","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-via-distribution-and","title":"DOMAIN ADAPTATION VIA DISTRIBUTION AND REPRESENTATION MATCHING: A CASE STUDY ON TRAINING DATA SELECTION VIA REINFORCEMENT LEARNING","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-learning-with-multi-domain","title":"Semi-supervised Learning with Multi-Domain Sentiment Word Embeddings","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-adversarial-invariance","title":"Unsupervised Adversarial Invariance","date":"2018-09-26","arxiv_id":"1809.10083","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-in-robot-fault-diagnostic","title":"Domain Adaptation for Robot Predictive Maintenance Systems","date":"2018-09-23","arxiv_id":"1809.08626","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-deep-clinical-models-handle-real-world","title":"Understanding Behavior of Clinical Models under Domain Shifts","date":"2018-09-20","arxiv_id":"1809.07806","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-domain-adaptation-under-deep-label","title":"Deep Domain Adaptation under Deep Label Scarcity","date":"2018-09-20","arxiv_id":"1809.08097","repositories_listed":0,"syntology":null},{"url":null,"slug":"sensor-transfer-learning-optimal-sensor","title":"Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation","date":"2018-09-17","arxiv_id":"1809.06256","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-domain-agnostic-normalization-layer-for","title":"A Domain Agnostic Normalization Layer for Unsupervised Adversarial Domain Adaptation","date":"2018-09-14","arxiv_id":"1809.05298","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-two-step-learning-method-for-detecting","title":"A Two-Step Learning Method For Detecting Landmarks on Faces From Different Domains","date":"2018-09-12","arxiv_id":"1809.04621","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-structure-from-motion-from-motion","title":"Learning structure-from-motion from motion","date":"2018-09-12","arxiv_id":"1809.04471","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-based-on","title":"Unsupervised Domain Adaptation Based on Source-guided Discrepancy","date":"2018-09-11","arxiv_id":"1809.03839","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-adversarial-discriminative-domain","title":"Improved Techniques for Adversarial Discriminative Domain Adaptation","date":"2018-09-10","arxiv_id":"1809.03625","repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-person-re-identification-by-deep-1","slug":"unsupervised-person-re-identification-by-deep-1","title":"Unsupervised Person Re-identification by Deep Learning Tracklet Association","date":"2018-09-08","arxiv_id":"1809.02874","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-augmentation-for-spoken-language","title":"Data Augmentation for Spoken Language Understanding via Joint Variational Generation","date":"2018-09-07","arxiv_id":"1809.02305","repositories_listed":0,"syntology":null},{"url":null,"slug":"gritnet-2-real-time-student-performance","title":"Domain Adaptation for Real-Time Student Performance Prediction","date":"2018-09-07","arxiv_id":"1809.06686","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-target-unsupervised-domain-adaptation","title":"Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories","date":"2018-09-04","arxiv_id":"1809.00852","repositories_listed":0,"syntology":null},{"url":null,"slug":"penalizing-top-performers-conservative-loss","title":"Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation","date":"2018-09-04","arxiv_id":"1809.00903","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-ego-pose-estimation-via-imitation-learning","title":"3D Ego-Pose Estimation via Imitation Learning","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/auggan-cross-domain-adaptation-with-gan-based","slug":"auggan-cross-domain-adaptation-with-gan-based","title":"AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-transfer-through-deep-activation","title":"Domain transfer through deep activation matching","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-adaptive-knowledge-transfer-for","title":"Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"museum-exhibit-identification-challenge-for-1","title":"Museum Exhibit Identification Challenge for the Supervised Domain Adaptation and Beyond","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"93251928141840493d475d892efbcdb2b1adcd434e538115a73fffa741161ab5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}