Papers

Variational Inference for Crowdsourcing - 2012 http://papers.nips.cc/paper/4627-variational-inference-for-crowdsourcing

• algorithm

ANALYTIC METHODS FOR OPTIMIZING REALTIME CROWDSOURCING https://www.dropbox.com/sh/7z6807apw4se6n8/AADpVmjL_iMLw-Om3_PWhdMZa/1204.2995v1.pdf

• algorithm
• pays users

Dynamic Bayesian Combination of Multiple Imperfect Classifiers https://www.dropbox.com/sh/7z6807apw4se6n8/AADKZXbcflGzwQFs6p2HZHZfa/1206.1831v1.pdf

• algorithm

Manuscript Transcription by Crowdsourcing: Transcribe Bentham https://www.dropbox.com/sh/7z6807apw4se6n8/AADWDxntOA4Ac9XZE5ovRJCka/7999-12071-1-PB.pdf

• project description (no algorithm)

Message-passing Methods on Loopy Factor Graphs Based on Homotopy and Reweighting https://www.dropbox.com/sh/7z6807apw4se6n8/AAB-3RKcc1xHNHDzUg4uTF5na/159415.pdf

• techniques

Error Rate Analysis of Labeling by Crowdsourcing https://www.dropbox.com/sh/7z6807apw4se6n8/AACsDwJnhPDTRnCqdsWl1vqTa/ActivePaper4_bak.pdf

• theoretical analysis of error rates

Crowds in Two Seconds: Enabling Realtime Crowd-Powered Interfaces https://www.dropbox.com/sh/7z6807apw4se6n8/AAAAnE2wH234Q-iaD9KoA4Uta/adrenaline-uist2011.pdf

• algorithm
• partially by paying users

Efficient Budget Allocation with Accuracy Guarantees for Crowdsourcing Classification Tasks https://www.dropbox.com/sh/7z6807apw4se6n8/AAAawyKTQpd9Q-2odU9so_lya/crowdverify_final.pdf

• algorithm
• pays user

Low-Complexity Message-Passing Algorithms for Distributed Computation https://www.dropbox.com/sh/7z6807apw4se6n8/AACEyWIYgr9nXRzJzFyAMf-ma/EECS-2013-53%281%29.pdf

• techniques

Adaptive Task Assignment for Crowdsourced Classification https://www.dropbox.com/sh/7z6807apw4se6n8/AADePQ5kyOZUl8_Nr0wbMTbja/ICML2013_ho13.pdf

• algorithm - task assignment

Approximate Bayesian recursive estimation https://www.dropbox.com/sh/7z6807apw4se6n8/AAB7UhDbi4dcYlHVVdvRXRqqa/karny-0425539.pdf

• technique

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy https://www.dropbox.com/sh/7z6807apw4se6n8/AACjxKs7_c735TH1RRXhxWC2a/ordinal-crowd.pdf

• algorithm

Pairwise Ranking Aggregation in a Crowdsourced Setting https://www.dropbox.com/sh/7z6807apw4se6n8/AABiupSQGjqjfChukVOivIT7a/p193-chen.pdf

• algorithm for pairwise rankings

Aggregating Crowdsourced Binary Ratings https://www.dropbox.com/sh/7z6807apw4se6n8/AAB1_0fdwxZGdR637uUsjddOa/p285-dalvi.pdf

• algorithm and theorteical bounds

Efficient Crowdsourcing for Multi-class Labeling https://www.dropbox.com/sh/7z6807apw4se6n8/AAAz7Z_NIyKURHjtadwnxTr0a/paper_crowdsourcing_sigmetrics.pdf

• algorithm for multi-class labels

Minimax Optimal Convergence Rates for Estimating Ground Truth from Crowdsourced Labels https://www.dropbox.com/sh/7z6807apw4se6n8/AAA_bYns9Un3HrouUBI3K2eja/paper-OneCoin-02052014.pdf

• theoretical rates

Crowd IQ: Measuring the Intelligence of Crowdsourcing Platforms https://www.dropbox.com/sh/7z6807apw4se6n8/AAB2s3dIcSTpZVkyoNcE-WKea/WebSci2012.pdf

• theoretical rates for paying

Dynamic estimation of worker reliability in crowdsourcing for regression tasks: Making it work http://www.sciencedirect.com/science/article/pii/S0957417414002097

Learning from multiple annotators: Distinguishing good from random labelers http://www.sciencedirect.com/science/article/pii/S016786551300202X

Using objective ground-truth labels created by multiple annotators for improved video classification: A comparative study http://www.sciencedirect.com/science/article/pii/S107731421300129X

Near-Optimally Teaching the Crowd to Classify

Community-based bayesian aggregation models for crowdsourcing On Actively Teaching the Crowd to Classify http://dl.acm.org/citation.cfm?id=2567989