{"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/distributed-computing/papers/4","list_of":"/task/distributed-computing","task":"Distributed Computing","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":4,"pages_in_order":4,"rows_per_page":100,"rows":[301,379],"of":379,"counts":{"archive_papers_tagged":379,"with_a_code_link":85,"where_syntology_ran_a_sample":12,"not_listed_spam_title":0,"listed":379,"listed_where_code_ran":12,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":12,"every_run_a_failure_of_syntologys_instrument":0,"listed_with_a_run_with_no_instrument_failure":12,"listed_every_run_a_failure_of_syntologys_instrument":0,"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/distributed-computing","prev":"/task/distributed-computing/papers/3","next":null,"papers":[{"url":null,"slug":"partitioned-variational-inference-a-unified","title":"Partitioned Variational Inference: A unified framework encompassing federated and continual learning","date":"2018-11-27","arxiv_id":"1811.11206","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-gradient-descent-with-coded","title":"Distributed Gradient Descent with Coded Partial Gradient Computations","date":"2018-11-22","arxiv_id":"1811.09271","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-creating-subsurface-camera","title":"Toward Creating Subsurface Camera","date":"2018-10-29","arxiv_id":"1810.12271","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-efficient-parallel-algorithms","title":"Communication Efficient Parallel Algorithms for Optimization on Manifolds","date":"2018-10-26","arxiv_id":"1810.11155","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantile-regression-under-memory-constraint","title":"Quantile Regression Under Memory Constraint","date":"2018-10-18","arxiv_id":"1810.08264","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bi-layered-parallel-training-architecture","title":"A Bi-layered Parallel Training Architecture for Large-scale Convolutional Neural Networks","date":"2018-10-17","arxiv_id":"1810.07742","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-periodicity-based-parallel-time-series","title":"A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments","date":"2018-10-17","arxiv_id":"1810.07776","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-droplet-approach-based-on-raptor-codes-for","title":"A Droplet Approach Based on Raptor Codes for Distributed Computing With Straggling Servers","date":"2018-10-08","arxiv_id":"1810.03488","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicate-learning-in-neural-systems","title":"Predicate learning in neural systems: Discovering latent generative structures","date":"2018-10-02","arxiv_id":"1810.01127","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automated-neural-design-an-open","title":"Towards automated neural design: An open source, distributed neural architecture research framework","date":"2018-09-20","arxiv_id":"1810.08648","repositories_listed":0,"syntology":null},{"url":null,"slug":"left-ventricle-segmentation-and-volume","title":"Left Ventricle Segmentation and Volume Estimation on Cardiac MRI using Deep Learning","date":"2018-09-14","arxiv_id":"1809.06247","repositories_listed":0,"syntology":null},{"url":null,"slug":"paryopt-a-software-for-parallel-asynchronous","title":"PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization","date":"2018-09-12","arxiv_id":"1809.04668","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-mapreduce-based-big-data-framework-for","title":"A MapReduce based Big-data Framework for Object Extraction from Mosaic Satellite Images","date":"2018-08-26","arxiv_id":"1808.08528","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-effect-of-task-to-worker-assignment-in","title":"On the Effect of Task-to-Worker Assignment in Distributed Computing Systems with Stragglers","date":"2018-08-08","arxiv_id":"1808.02838","repositories_listed":0,"syntology":null},{"url":null,"slug":"holographic-automata-for-ambient-immersive-a","title":"Holographic Automata for Ambient Immersive A. I. via Reservoir Computing","date":"2018-06-09","arxiv_id":"1806.05108","repositories_listed":0,"syntology":null},{"url":null,"slug":"predictive-performance-modeling-for","title":"Predictive Performance Modeling for Distributed Computing using Black-Box Monitoring and Machine Learning","date":"2018-05-30","arxiv_id":"1805.11877","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-gradient-descent-via-moment-encoding","title":"Robust Gradient Descent via Moment Encoding with LDPC Codes","date":"2018-05-22","arxiv_id":"1805.08327","repositories_listed":0,"syntology":null},{"url":null,"slug":"falsification-of-cyber-physical-systems-using","title":"Falsification of Cyber-Physical Systems Using Deep Reinforcement Learning","date":"2018-05-01","arxiv_id":"1805.00200","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-on-operational-facility-data","title":"Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows","date":"2018-04-17","arxiv_id":"1804.06062","repositories_listed":0,"syntology":null},{"url":null,"slug":"bigsr-an-empirical-study-of-real-time","title":"BigSR: an empirical study of real-time expressive RDF stream reasoning on modern Big Data platforms","date":"2018-04-12","arxiv_id":"1804.04367","repositories_listed":0,"syntology":null},{"url":null,"slug":"fundamental-resource-trade-offs-for-encoded","title":"Fundamental Resource Trade-offs for Encoded Distributed Optimization","date":"2018-03-31","arxiv_id":"1804.00217","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-stochastic-large-scale-machine-learning","title":"A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations","date":"2018-03-29","arxiv_id":"1803.11287","repositories_listed":0,"syntology":null},{"url":null,"slug":"block-diagonal-and-lt-codes-for-distributed","title":"Block-Diagonal and LT Codes for Distributed Computing With Straggling Servers","date":"2017-12-21","arxiv_id":"1712.08230","repositories_listed":0,"syntology":null},{"url":null,"slug":"coded-distributed-computing-for-inverse","title":"Coded Distributed Computing for Inverse Problems","date":"2017-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modular-resource-centric-learning-for","title":"Modular Resource Centric Learning for Workflow Performance Prediction","date":"2017-11-15","arxiv_id":"1711.05429","repositories_listed":0,"syntology":null},{"url":null,"slug":"dscovr-randomized-primal-dual-block","title":"DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization","date":"2017-10-13","arxiv_id":"1710.05080","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimensionality-reduction-ensembles","title":"Dimensionality Reduction Ensembles","date":"2017-10-11","arxiv_id":"1710.04484","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-very-large-scale-bundle","title":"Distributed Very Large Scale Bundle Adjustment by Global Camera Consensus","date":"2017-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"giant-globally-improved-approximate-newton","title":"GIANT: Globally Improved Approximate Newton Method for Distributed Optimization","date":"2017-09-11","arxiv_id":"1709.03528","repositories_listed":0,"syntology":null},{"url":null,"slug":"artificial-life-complex-systems-and-cloud","title":"Artificial life, complex systems and cloud computing: a short review","date":"2017-09-02","arxiv_id":"1710.02553","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-robust-multi-batch-l-bfgs-method-for","title":"A Robust Multi-Batch L-BFGS Method for Machine Learning","date":"2017-07-26","arxiv_id":"1707.08552","repositories_listed":0,"syntology":null},{"url":null,"slug":"proceedings-sixteenth-conference-on","title":"Proceedings Sixteenth Conference on Theoretical Aspects of Rationality and Knowledge","date":"2017-07-25","arxiv_id":"1707.08250","repositories_listed":0,"syntology":null},{"url":null,"slug":"remote-sensing-of-forests-using-discrete","title":"Remote sensing of forests using discrete return airborne LiDAR","date":"2017-07-17","arxiv_id":"1707.09865","repositories_listed":0,"syntology":null},{"url":null,"slug":"asynchronous-announcements","title":"Asynchronous Announcements","date":"2017-05-08","arxiv_id":"1705.03392","repositories_listed":0,"syntology":null},{"url":null,"slug":"parallelized-kendalls-tau-coefficient","title":"Parallelized Kendall's Tau Coefficient Computation via SIMD Vectorized Sorting On Many-Integrated-Core Processors","date":"2017-04-12","arxiv_id":"1704.03767","repositories_listed":0,"syntology":null},{"url":null,"slug":"block-cur-decomposing-matrices-using-groups","title":"Block CUR: Decomposing Matrices using Groups of Columns","date":"2017-03-17","arxiv_id":"1703.06065","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-scale-evolution-of-convolutional-neural","title":"Large Scale Evolution of Convolutional Neural Networks Using Volunteer Computing","date":"2017-03-15","arxiv_id":"1703.05422","repositories_listed":0,"syntology":null},{"url":null,"slug":"akid-a-library-for-neural-network-research","title":"Akid: A Library for Neural Network Research and Production from a Dataism Approach","date":"2017-01-03","arxiv_id":"1701.00609","repositories_listed":0,"syntology":null},{"url":null,"slug":"folksodrivencloud-an-annotation-and-process","title":"FolksoDrivenCloud: an annotation and process application for social collaborative networking","date":"2016-12-30","arxiv_id":"1612.09572","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-real-time-sentiment-analysis-for","title":"Distributed Real-Time Sentiment Analysis for Big Data Social Streams","date":"2016-12-27","arxiv_id":"1612.08543","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-distributed-sparse-regression-a","title":"Feature-distributed sparse regression: a screen-and-clean approach","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"short-dot-computing-large-linear-transforms","title":"Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"online-learning-for-wireless-distributed","title":"Online Learning for Wireless Distributed Computing","date":"2016-11-09","arxiv_id":"1611.02830","repositories_listed":0,"syntology":null},{"url":null,"slug":"computational-tradeoffs-in-biological-neural","title":"Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks","date":"2016-10-06","arxiv_id":"1610.02084","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-primer-on-coordinate-descent-algorithms","title":"A Primer on Coordinate Descent Algorithms","date":"2016-09-30","arxiv_id":"1610.00040","repositories_listed":0,"syntology":null},{"url":null,"slug":"horn-a-system-for-parallel-training-and","title":"Horn: A System for Parallel Training and Regularizing of Large-Scale Neural Networks","date":"2016-08-02","arxiv_id":"1608.00781","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-graph-clustering-by-load","title":"Distributed Graph Clustering by Load Balancing","date":"2016-07-18","arxiv_id":"1607.04984","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-distributed-deep-representation-learning","title":"A Distributed Deep Representation Learning Model for Big Image Data Classification","date":"2016-07-02","arxiv_id":"1607.00501","repositories_listed":0,"syntology":null},{"url":null,"slug":"proceedings-fifteenth-conference-on","title":"Proceedings Fifteenth Conference on Theoretical Aspects of Rationality and Knowledge","date":"2016-06-23","arxiv_id":"1606.07295","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-anthropo-inspired-computational","title":"Towards Anthropo-inspired Computational Systems: the $P^3$ Model","date":"2016-06-10","arxiv_id":"1606.03229","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-batch-l-bfgs-method-for-machine","title":"A Multi-Batch L-BFGS Method for Machine Learning","date":"2016-05-19","arxiv_id":"1605.06049","repositories_listed":0,"syntology":null},{"url":null,"slug":"loh-and-behold-web-scale-visual-search","title":"LOH and behold: Web-scale visual search, recommendation and clustering using Locally Optimized Hashing","date":"2016-04-21","arxiv_id":"1604.06480","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepspark-a-spark-based-distributed-deep","title":"DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters","date":"2016-02-26","arxiv_id":"1602.08191","repositories_listed":0,"syntology":null},{"url":null,"slug":"nodio-a-javascript-framework-for-volunteer","title":"NodIO, a JavaScript framework for volunteer-based evolutionary algorithms : first results","date":"2016-01-07","arxiv_id":"1601.01607","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-distributed-k-center-clustering-with","title":"Fast Distributed k-Center Clustering with Outliers on Massive Data","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-agent-system-approach-to-load","title":"A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing","date":"2015-09-21","arxiv_id":"1509.06420","repositories_listed":0,"syntology":null},{"url":null,"slug":"tag-weighted-topic-model-for-large-scale-semi","title":"Tag-Weighted Topic Model For Large-scale Semi-Structured Documents","date":"2015-07-30","arxiv_id":"1507.08396","repositories_listed":0,"syntology":null},{"url":null,"slug":"splash-user-friendly-programming-interface","title":"Splash: User-friendly Programming Interface for Parallelizing Stochastic Algorithms","date":"2015-06-24","arxiv_id":"1506.07552","repositories_listed":0,"syntology":null},{"url":null,"slug":"cloudcv-large-scale-distributed-computer","title":"CloudCV: Large Scale Distributed Computer Vision as a Cloud Service","date":"2015-06-12","arxiv_id":"1506.04130","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-asynchronous-mini-batch-algorithm-for","title":"An Asynchronous Mini-Batch Algorithm for Regularized Stochastic Optimization","date":"2015-05-18","arxiv_id":"1505.04824","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-partitioning-via-parallel-submodular","title":"Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning","date":"2015-05-18","arxiv_id":"1505.04636","repositories_listed":0,"syntology":null},{"url":null,"slug":"unwrapping-admm-efficient-distributed","title":"Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction","date":"2015-04-08","arxiv_id":"1504.02147","repositories_listed":0,"syntology":null},{"url":null,"slug":"communication-efficient-distributed","title":"Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss","date":"2015-01-01","arxiv_id":"1501.00263","repositories_listed":0,"syntology":null},{"url":null,"slug":"big-learning-with-bayesian-methods","title":"Big Learning with Bayesian Methods","date":"2014-11-24","arxiv_id":"1411.6370","repositories_listed":0,"syntology":null},{"url":null,"slug":"fgpga-an-efficient-genetic-approach-for","title":"FGPGA: An Efficient Genetic Approach for Producing Feasible Graph Partitions","date":"2014-11-17","arxiv_id":"1411.4379","repositories_listed":0,"syntology":null},{"url":null,"slug":"n3lars-minimum-redundancy-maximum-relevance","title":"N$^3$LARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data","date":"2014-11-10","arxiv_id":"1411.2331","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-distributed-principal-component","title":"Improved Distributed Principal Component Analysis","date":"2014-08-25","arxiv_id":"1408.5823","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-protein-dynamics-with-l1","title":"Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models","date":"2014-05-06","arxiv_id":"1405.1444","repositories_listed":0,"syntology":null},{"url":null,"slug":"chemlambda-universality-and-self","title":"Chemlambda, universality and self-multiplication","date":"2014-03-31","arxiv_id":"1403.8046","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-dynamic-job-scheduling-in-grid","title":"A Survey on Dynamic Job Scheduling in Grid Environment Based on Heuristic Algorithms","date":"2014-02-21","arxiv_id":"1402.5205","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-reasoning-in-modal-and-description","title":"Automated Reasoning in Modal and Description Logics via SAT Encoding: the Case Study of K(m)/ALC-Satisfiability","date":"2014-01-15","arxiv_id":"1401.3463","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-aware-dynamic-scheduler-for","title":"Structure-Aware Dynamic Scheduler for Parallel Machine Learning","date":"2013-12-19","arxiv_id":"1312.5766","repositories_listed":0,"syntology":null},{"url":null,"slug":"embed-and-conquer-scalable-embeddings-for","title":"Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce","date":"2013-11-11","arxiv_id":"1311.2334","repositories_listed":0,"syntology":null},{"url":null,"slug":"linearized-alternating-direction-method-with","title":"Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty for Separable Convex Programs in Machine Learning","date":"2013-10-18","arxiv_id":"1310.5035","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-estimating-total-time-to-solve-sat-in","title":"On estimating total time to solve SAT in distributed computing environments: Application to the SAT@home project","date":"2013-08-04","arxiv_id":"1308.0761","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditions-for-convergence-in-regularized","title":"Conditions for Convergence in Regularized Machine Learning Objectives","date":"2013-05-17","arxiv_id":"1305.4081","repositories_listed":0,"syntology":null},{"url":null,"slug":"link-prediction-with-social-vector-clocks","title":"Link Prediction with Social Vector Clocks","date":"2013-04-15","arxiv_id":"1304.4058","repositories_listed":0,"syntology":null},{"url":null,"slug":"cellular-tree-classifiers","title":"Cellular Tree Classifiers","date":"2013-01-20","arxiv_id":"1301.4679","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributed-matrix-completion-and-robust","title":"Distributed Matrix Completion and Robust Factorization","date":"2011-07-05","arxiv_id":"1107.0789","repositories_listed":0,"syntology":null}],"record_sha256":"d1a011ecbac998416fd2ba16cf2c544011959eec057b96ffc433e70c3125ae93","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}