{"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/mixture-of-experts/papers/14","list_of":"/task/mixture-of-experts","task":"Mixture-of-Experts","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":14,"pages_in_order":14,"rows_per_page":100,"rows":[1301,1312],"of":1312,"counts":{"archive_papers_tagged":1312,"with_a_code_link":516,"where_syntology_ran_a_sample":216,"not_listed_spam_title":0,"listed":1312,"listed_where_code_ran":216,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":184,"every_run_a_failure_of_syntologys_instrument":32,"listed_with_a_run_with_no_instrument_failure":184,"listed_every_run_a_failure_of_syntologys_instrument":32,"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/mixture-of-experts","prev":"/task/mixture-of-experts/papers/13","next":null,"papers":[{"url":null,"slug":"a-universal-approximation-theorem-for-mixture","title":"A Universal Approximation Theorem for Mixture of Experts Models","date":"2016-02-11","arxiv_id":"1602.03683","repositories_listed":0,"syntology":null},{"url":null,"slug":"addressing-complex-and-subjective-product","title":"Addressing Complex and Subjective Product-Related Queries with Customer Reviews","date":"2015-12-21","arxiv_id":"1512.06863","repositories_listed":0,"syntology":null},{"url":null,"slug":"mediated-experts-for-deep-convolutional","title":"Mediated Experts for Deep Convolutional Networks","date":"2015-11-19","arxiv_id":"1511.06072","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-speech-recognition-using-neural","title":"類神經網路訓練結合環境群集及專家混合系統於強健性語音辨識(Automatic Speech Recognition using Neural Network based Acoustic Model with the Environment Clustering and Mixture of Experts Algorithms) [In Chinese]","date":"2015-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-large-scale-video-classification","title":"Efficient Large Scale Video Classification","date":"2015-05-22","arxiv_id":"1505.06250","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-mixture-of-experts-model-for","title":"Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression","date":"2014-12-09","arxiv_id":"1412.3078","repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-feature-and-expert-selection","title":"Simultaneous Feature and Expert Selection within Mixture of Experts","date":"2014-05-29","arxiv_id":"1405.7624","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-tuned-visual-subclass-learning-with","title":"Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach","date":"2014-05-22","arxiv_id":"1405.5732","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-factored-representations-in-a-deep","title":"Learning Factored Representations in a Deep Mixture of Experts","date":"2013-12-16","arxiv_id":"1312.4314","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-approach-to-universal-prediction","title":"A Unified Approach to Universal Prediction: Generalized Upper and Lower Bounds","date":"2013-11-25","arxiv_id":"1311.6396","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-hierarchical-mixtures-of-experts","title":"Bayesian Hierarchical Mixtures of Experts","date":"2012-10-19","arxiv_id":"1212.2447","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-mixture-of-gaussian-process","title":"Variational Mixture of Gaussian Process Experts","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"8a137dabf06723268d5a4d3afb44bafb9865455a660c9e5d9cd1b220003f3c70","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}