<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>1 on Sebastian Schelter</title>
    <link>https://ssc.io/publication_types/1/</link>
    <description>Recent content in 1 on Sebastian Schelter</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-us</language>
    <copyright>&amp;copy; 2020</copyright>
    <lastBuildDate>Sun, 16 May 2021 00:00:00 +0000</lastBuildDate>
    
	<atom:link href="https://ssc.io/publication_types/1/index.xml" rel="self" type="application/rss+xml" />
    
    
    <item>
      <title>Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression</title>
      <link>https://ssc.io/publication/probabilistic-gradient-boosting-machines-for-large-scale-probabilistic-regression-kdd/</link>
      <pubDate>Sun, 16 May 2021 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/probabilistic-gradient-boosting-machines-for-large-scale-probabilistic-regression-kdd/</guid>
      <description></description>
    </item>
    
    <item>
      <title>HedgeCut: Maintaining Randomised Trees for Low-Latency Machine Unlearning</title>
      <link>https://ssc.io/publication/hedgecut-maintaining-randomized-trees-for-low-latency-machine-unlearning-sigmod/</link>
      <pubDate>Wed, 10 Mar 2021 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/hedgecut-maintaining-randomized-trees-for-low-latency-machine-unlearning-sigmod/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Learnings from a Retail Recommendation System on Billions of Interactions at bol.com</title>
      <link>https://ssc.io/publication/learnings-from-a-retail-recommendation-system-on-billions-of-interactions-icde/</link>
      <pubDate>Fri, 19 Feb 2021 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/learnings-from-a-retail-recommendation-system-on-billions-of-interactions-icde/</guid>
      <description></description>
    </item>
    
    <item>
      <title>mlinspect: a Data Distribution Debugger for Machine Learning Pipelines</title>
      <link>https://ssc.io/publication/identifying-data-distribution-bugs-in-ml-pipelines-with-mlinspect-sigmod-demo/</link>
      <pubDate>Thu, 18 Feb 2021 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/identifying-data-distribution-bugs-in-ml-pipelines-with-mlinspect-sigmod-demo/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Automating Data Quality Validation for Dynamic Data Ingestion</title>
      <link>https://ssc.io/publication/automating-data-quality-validation-for-dynamic-data-ingestion-edbt/</link>
      <pubDate>Thu, 21 Jan 2021 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/automating-data-quality-validation-for-dynamic-data-ingestion-edbt/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Jenga - A Framework to Study the Impact of Data Errors on the Predictions of Machine Learning Models</title>
      <link>https://ssc.io/publication/jenga-a-framework-to-study-the-impact-of-data-errors-on-ml-models-edbt/</link>
      <pubDate>Wed, 23 Dec 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/jenga-a-framework-to-study-the-impact-of-data-errors-on-ml-models-edbt/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines</title>
      <link>https://ssc.io/publication/mlinspect-lightweight-inspection-of-data-preprocessing-in-native-machine-learning-pipelines/</link>
      <pubDate>Thu, 15 Oct 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/mlinspect-lightweight-inspection-of-data-preprocessing-in-native-machine-learning-pipelines/</guid>
      <description></description>
    </item>
    
    <item>
      <title>RetaiL: Open your own grocery store to reduce waste</title>
      <link>https://ssc.io/publication/retail-open-your-own-grocery-store-to-reduce-waste-neurips-demo/</link>
      <pubDate>Sat, 03 Oct 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/retail-open-your-own-grocery-store-to-reduce-waste-neurips-demo/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Demand Forecasting in the Presence of Privileged Information</title>
      <link>https://ssc.io/publication/demand-forecasting-in-the-presence-of-privileged-information-aaltd-ecml-pkdd/</link>
      <pubDate>Thu, 16 Jul 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/demand-forecasting-in-the-presence-of-privileged-information-aaltd-ecml-pkdd/</guid>
      <description></description>
    </item>
    
    <item>
      <title>A Comparison of Supervised Learning to Match Methods for Product Search</title>
      <link>https://ssc.io/publication/a-comparison-of-supervised-learning-to-match-methods-for-product-search-sigir-ecom/</link>
      <pubDate>Sat, 11 Jul 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/a-comparison-of-supervised-learning-to-match-methods-for-product-search-sigir-ecom/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers</title>
      <link>https://ssc.io/publication/analyzing-and-predicting-purchase-intent-in-e-commerce-anonymous-vs-identified-customers-sigir-ecom/</link>
      <pubDate>Fri, 10 Jul 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/analyzing-and-predicting-purchase-intent-in-e-commerce-anonymous-vs-identified-customers-sigir-ecom/</guid>
      <description></description>
    </item>
    
    <item>
      <title>AlphaJoin: Join Order Selection à la AlphaGo</title>
      <link>https://ssc.io/publication/alphajoin-join-order-selection-a-la-alpha-go-vldb-phd/</link>
      <pubDate>Tue, 26 May 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/alphajoin-join-order-selection-a-la-alpha-go-vldb-phd/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Fairness-Aware Instrumentation of Preprocessing Pipelines for Machine Learning</title>
      <link>https://ssc.io/publication/fairness-aware-instrumentation-of-preprocessing-pipelines-forml-hilda20/</link>
      <pubDate>Mon, 27 Apr 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/fairness-aware-instrumentation-of-preprocessing-pipelines-forml-hilda20/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Elastic Machine Learning Algorithms in Amazon SageMaker</title>
      <link>https://ssc.io/publication/elastic-machine-learning-algorithms-in-amazon-sagemaker-sigmod/</link>
      <pubDate>Tue, 25 Feb 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/elastic-machine-learning-algorithms-in-amazon-sagemaker-sigmod/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Learning to Validate the Predictions of Black Box Classifiers on Unseen Data</title>
      <link>https://ssc.io/publication/learning-to-validate-the-predictions-of-black-box-classifiers-on-unseen-data-sigmod/</link>
      <pubDate>Mon, 20 Jan 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/learning-to-validate-the-predictions-of-black-box-classifiers-on-unseen-data-sigmod/</guid>
      <description></description>
    </item>
    
    <item>
      <title>FairPrep: Promoting Data to a First-Class Citizen in Studies on Fairness-Enhancing Interventions</title>
      <link>https://ssc.io/publication/fairprep-promoting-data-to-a-first-class-citizen-in-studies-on-fairness-enhancing-interventions-edbt/</link>
      <pubDate>Fri, 17 Jan 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/fairprep-promoting-data-to-a-first-class-citizen-in-studies-on-fairness-enhancing-interventions-edbt/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Zooming Out on an Evolving Graph</title>
      <link>https://ssc.io/publication/zooming-out-on-an-evolving-graph-edbt/</link>
      <pubDate>Wed, 15 Jan 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/zooming-out-on-an-evolving-graph-edbt/</guid>
      <description></description>
    </item>
    
    <item>
      <title>&#39;Amnesia&#39; - A Selection of Machine Learning Models That Can Forget User Data Very Fast</title>
      <link>https://ssc.io/publication/amnesia-a-selection-of-machine-learning-models-that-can-forget-user-data-very-fast-cidr/</link>
      <pubDate>Sun, 05 Jan 2020 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/amnesia-a-selection-of-machine-learning-models-that-can-forget-user-data-very-fast-cidr/</guid>
      <description></description>
    </item>
    
    <item>
      <title>AdaBench - Towards an Industry Standard Benchmark for Advanced Analytics</title>
      <link>https://ssc.io/publication/adabench-towards-an-industry-standard-benchmark-for-advanced-analytics-tpctc/</link>
      <pubDate>Mon, 01 Jul 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/adabench-towards-an-industry-standard-benchmark-for-advanced-analytics-tpctc/</guid>
      <description></description>
    </item>
    
    <item>
      <title>An Intermediate Representation for Optimizing Machine Learning Pipelines</title>
      <link>https://ssc.io/publication/optimizing-end-to-end-machine-learning-pipelines-for-model-training-vldb/</link>
      <pubDate>Mon, 01 Jul 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/optimizing-end-to-end-machine-learning-pipelines-for-model-training-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>&#39;Amnesia&#39; - Towards Machine Learning Models That Can Forget User Data Very Fast</title>
      <link>https://ssc.io/publication/amnesia-towards-machine-learning-models-that-can-forget-user-data-very-fast-applied-ai-for-database-systems-and-applications-vldb/</link>
      <pubDate>Sun, 23 Jun 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/amnesia-towards-machine-learning-models-that-can-forget-user-data-very-fast-applied-ai-for-database-systems-and-applications-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Efficient Incremental Cooccurrence Analysis for Item-Based Collaborative Filtering</title>
      <link>https://ssc.io/publication/efficient-incremental-cooccurrence-analysis-for-item-based-collaborative-filtering-ssdbm/</link>
      <pubDate>Fri, 03 May 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/efficient-incremental-cooccurrence-analysis-for-item-based-collaborative-filtering-ssdbm/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data</title>
      <link>https://ssc.io/publication/learning-to-validate-the-predictions-of-black-box-machine-learning-models-on-unseen-data-hilda19/</link>
      <pubDate>Fri, 19 Apr 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/learning-to-validate-the-predictions-of-black-box-machine-learning-models-on-unseen-data-hilda19/</guid>
      <description></description>
    </item>
    
    <item>
      <title>DEEM 2019: Workshop on Data Management for End-to-End Machine Learning</title>
      <link>https://ssc.io/publication/deem19-workshop-on-data-management-for-end-to-end-machine-learning-sigmod/</link>
      <pubDate>Sun, 07 Apr 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/deem19-workshop-on-data-management-for-end-to-end-machine-learning-sigmod/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Differential Data Quality Verification on Partitioned Data</title>
      <link>https://ssc.io/publication/differential-data-quality-verification-on-partitioned-data-icde/</link>
      <pubDate>Mon, 01 Apr 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/differential-data-quality-verification-on-partitioned-data-icde/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Unit Testing Data with Deequ</title>
      <link>https://ssc.io/publication/unit-testing-data-with-deequ-sigmod/</link>
      <pubDate>Wed, 13 Mar 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/unit-testing-data-with-deequ-sigmod/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Data-Related Challenges in End-to-End Machine Learning</title>
      <link>https://ssc.io/publication/data-related-challenges-in-end-to-end-machine-learning-north-east-database-day/</link>
      <pubDate>Thu, 10 Jan 2019 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/data-related-challenges-in-end-to-end-machine-learning-north-east-database-day/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Deequ - Data Quality Validation for Machine Learning Pipelines</title>
      <link>https://ssc.io/publication/deequ-data-quality-validation-for-machine-learning-pipelines-mlsystems-nips/</link>
      <pubDate>Wed, 07 Nov 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/deequ-data-quality-validation-for-machine-learning-pipelines-mlsystems-nips/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Deep Learning for Missing Value Imputation in Tables with Non-Numerical Data</title>
      <link>https://ssc.io/publication/deep-learning-for-missing-value-imputation-in-tables-with-non-numerical-data-cikm/</link>
      <pubDate>Mon, 01 Oct 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/deep-learning-for-missing-value-imputation-in-tables-with-non-numerical-data-cikm/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Benchmarking Distributed Data Processing Systems for Machine Learning Workloads</title>
      <link>https://ssc.io/publication/benchmarking-distributed-data-processing-systems-tpctc-vldb/</link>
      <pubDate>Sat, 01 Sep 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/benchmarking-distributed-data-processing-systems-tpctc-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Automating Large-Scale Data Quality Verification</title>
      <link>https://ssc.io/publication/automating-large-scale-data-quality-verification-vldb/</link>
      <pubDate>Mon, 27 Aug 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/automating-large-scale-data-quality-verification-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>BlockJoin: Efficient Matrix Partitioning Through Joins</title>
      <link>https://ssc.io/publication/blockjoin-efficient-matrix-partitioning-through-joins-vldb/</link>
      <pubDate>Mon, 27 Aug 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/blockjoin-efficient-matrix-partitioning-through-joins-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Declarative Metadata Management: A Missing Piece in End-to-End Machine Learning</title>
      <link>https://ssc.io/publication/declarative-metadata-anagement-a-missing-piece-in-end-to-end-machine-learning-sysml/</link>
      <pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/declarative-metadata-anagement-a-missing-piece-in-end-to-end-machine-learning-sysml/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Automatically Tracking Metadata and Provenance of Machine Learning Experiments</title>
      <link>https://ssc.io/publication/automatically-tracking-metadata-and-provenance-of-machine-learning-experiments-mlsystems-nips/</link>
      <pubDate>Fri, 08 Dec 2017 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/automatically-tracking-metadata-and-provenance-of-machine-learning-experiments-mlsystems-nips/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Dark Germany: Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing</title>
      <link>https://ssc.io/publication/dark-germany-hidden-patterns-of-participation-in-online-far-right-protests-against-refugee-housing-socinfo/</link>
      <pubDate>Wed, 13 Sep 2017 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/dark-germany-hidden-patterns-of-participation-in-online-far-right-protests-against-refugee-housing-socinfo/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Probabilistic Demand Forecasting at Scale</title>
      <link>https://ssc.io/publication/probabilistic-demand-forecasting-at-scale-vldb/</link>
      <pubDate>Mon, 28 Aug 2017 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/probabilistic-demand-forecasting-at-scale-vldb/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Dark Germany: Hidden Patterns of Participation in Online Far-Right Protests Against Refugee Housing</title>
      <link>https://ssc.io/publication/dark-germany-temporal-characteristics-and-connectivity-patterns-in-online-far-right-protests-against-refugee-housing-websci/</link>
      <pubDate>Sun, 25 Jun 2017 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/dark-germany-temporal-characteristics-and-connectivity-patterns-in-online-far-right-protests-against-refugee-housing-websci/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Gilbert: Declarative Sparse Linear Algebra on Massively Parallel Dataflow Systems</title>
      <link>https://ssc.io/publication/gilbert-declarative-sparse-linear-algebra-on-massively-parallel-dataflow-systems-btw/</link>
      <pubDate>Mon, 06 Mar 2017 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/gilbert-declarative-sparse-linear-algebra-on-massively-parallel-dataflow-systems-btw/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Structural Patterns in the Rise of Germany’s New Right on Facebook</title>
      <link>https://ssc.io/publication/structural-patterns-in-the-rise-of-germanys-new-right-on-facebook-data-mining-in-politics-icdm/</link>
      <pubDate>Mon, 12 Dec 2016 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/structural-patterns-in-the-rise-of-germanys-new-right-on-facebook-data-mining-in-politics-icdm/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Samsara: Declarative Machine Learning on Distributed Dataflow Systems</title>
      <link>https://ssc.io/publication/samsara-declarative-machine-learning-on-distributed-dataflow-systems-mlsystems-nips/</link>
      <pubDate>Mon, 05 Dec 2016 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/samsara-declarative-machine-learning-on-distributed-dataflow-systems-mlsystems-nips/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Predicting Political Party Affiliation from Text</title>
      <link>https://ssc.io/publication/predicting-political-party-affiliation-from-text-poltext/</link>
      <pubDate>Tue, 14 Jun 2016 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/predicting-political-party-affiliation-from-text-poltext/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Tracking The Trackers: A Large-Scale Analysis of Embedded Web Trackers</title>
      <link>https://ssc.io/publication/tracking-the-trackers-a-large-scale-analysis-of-embedded-web-trackers-icwsm/</link>
      <pubDate>Wed, 18 May 2016 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/tracking-the-trackers-a-large-scale-analysis-of-embedded-web-trackers-icwsm/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Optimistic Recovery for Iterative Dataflows in Action</title>
      <link>https://ssc.io/publication/optimistic-recovery-for-iterative-dataflows-in-action-sigmod-demo/</link>
      <pubDate>Sun, 31 May 2015 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/optimistic-recovery-for-iterative-dataflows-in-action-sigmod-demo/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Efficient Sample Generation for Scalable Meta Learning</title>
      <link>https://ssc.io/publication/efficient-sample-generation-for-scalable-meta-learning-icde/</link>
      <pubDate>Mon, 13 Apr 2015 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/efficient-sample-generation-for-scalable-meta-learning-icde/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Factorbird - a Parameter Server Approach to Distributed Matrix Factorization</title>
      <link>https://ssc.io/publication/factorbird-a-parameter-server-approach-to-distributed-matrix-factorization-distributed-machine-learning-and-matrix-computations-nips/</link>
      <pubDate>Mon, 08 Dec 2014 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/factorbird-a-parameter-server-approach-to-distributed-matrix-factorization-distributed-machine-learning-and-matrix-computations-nips/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Scaling Data Mining in Massively Parallel Dataflow Systems</title>
      <link>https://ssc.io/publication/scaling-data-mining-in-massively-parallel-dataflow-systems-sigmod-phd-symposium/</link>
      <pubDate>Sun, 22 Jun 2014 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/scaling-data-mining-in-massively-parallel-dataflow-systems-sigmod-phd-symposium/</guid>
      <description></description>
    </item>
    
    <item>
      <title>&#39;All Roads Lead to Rome:&#39; Optimistic Recovery for Distributed Iterative Data Processing</title>
      <link>https://ssc.io/publication/all-roads-lead-to-rome-optimistic-recovery-for-distributed-iterative-data-processing-cikm/</link>
      <pubDate>Sun, 27 Oct 2013 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/all-roads-lead-to-rome-optimistic-recovery-for-distributed-iterative-data-processing-cikm/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Distributed Matrix Factorization with MapReduce using a series of Broadcast-Joins</title>
      <link>https://ssc.io/publication/distributed-matrix-factorization-with-mapreduce-using-a-series-of-broadcast-joins-recsys/</link>
      <pubDate>Sat, 12 Oct 2013 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/distributed-matrix-factorization-with-mapreduce-using-a-series-of-broadcast-joins-recsys/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Iterative Parallel Data Processing with Stratosphere: An Inside Look</title>
      <link>https://ssc.io/publication/iterative-parallel-data-processing-with-stratosphere-an-inside-look-sigmod-demo/</link>
      <pubDate>Sat, 22 Jun 2013 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/iterative-parallel-data-processing-with-stratosphere-an-inside-look-sigmod-demo/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Collaborative Filtering with Apache Mahout</title>
      <link>https://ssc.io/publication/collaborative-filtering-with-apache-mahout-recommender-systems-challenge-recsys/</link>
      <pubDate>Thu, 13 Sep 2012 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/collaborative-filtering-with-apache-mahout-recommender-systems-challenge-recsys/</guid>
      <description></description>
    </item>
    
    <item>
      <title>Scalable Similarity-Based Neighborhood Methods with MapReduce</title>
      <link>https://ssc.io/publication/scalable-similarity-based-neighborhood-methods-with-mapreduce-recsys/</link>
      <pubDate>Sun, 09 Sep 2012 00:00:00 +0000</pubDate>
      
      <guid>https://ssc.io/publication/scalable-similarity-based-neighborhood-methods-with-mapreduce-recsys/</guid>
      <description></description>
    </item>
    
  </channel>
</rss>