Co-regularized Multi-view Spectral Clustering
- Abhishek Kumar, Piyush Rai, Hal Daumé
- Computer ScienceNIPS
- 12 December 2011
A spectral clustering framework is proposed that achieves this goal by co-regularizing the clustering hypotheses, and two co- regularization schemes are proposed to accomplish this.
Frustratingly Easy Domain Adaptation
- Hal Daumé
- Computer ScienceAnnual Meeting of the Association for…
- 1 June 2007
We describe an approach to domain adaptation that is appropriate exactly in the case when one has enough “target” data to do slightly better than just using only “source” data. Our approach is…
Generalized Multiview Analysis: A discriminative latent space
- Abhishek Sharma, Abhishek Kumar, Hal Daumé, D. Jacobs
- Computer ScienceIEEE Conference on Computer Vision and Pattern…
- 16 June 2012
GMA solves a joint, relaxed QCQP over different feature spaces to obtain a single (non)linear subspace and is a supervised extension of Canonical Correlational Analysis (CCA), which is useful for cross-view classification and retrieval.
Deep Unordered Composition Rivals Syntactic Methods for Text Classification
- Mohit Iyyer, Varun Manjunatha, Jordan L. Boyd-Graber, Hal Daumé
- Computer ScienceAnnual Meeting of the Association for…
- 1 July 2015
This work presents a simple deep neural network that competes with and, in some cases, outperforms such models on sentiment analysis and factoid question answering tasks while taking only a fraction of the training time.
A Co-training Approach for Multi-view Spectral Clustering
- Abhishek Kumar, Hal Daumé
- Computer ScienceInternational Conference on Machine Learning
- 28 June 2011
A spectral clustering algorithm for the multi-view setting where the authors have access to multiple views of the data, each of which can be independently used for clustering, which has a flavor of co-training.
Datasheets for datasets
- Timnit Gebru, Jamie Morgenstern, Kate Crawford
- Computer ScienceCommunications of the ACM
- 23 March 2018
Documentation to facilitate communication between dataset creators and consumers and consumers is presented.
Search-based structured prediction
- Hal Daumé, J. Langford, D. Marcu
- Computer ScienceMachine-mediated learning
- 1 June 2009
Searn is an algorithm for integrating search and learning to solve complex structured prediction problems such as those that occur in natural language, speech, computational biology, and vision and comes with a strong, natural theoretical guarantee: good performance on the derived classification problems implies goodperformance on the structured prediction problem.
Learning Task Grouping and Overlap in Multi-task Learning
- Abhishek Kumar, Hal Daumé
- Computer ScienceInternational Conference on Machine Learning
- 26 June 2012
This work proposes a framework for multi-task learning that enables one to selectively share the information across the tasks, based on the assumption that task parameters within a group lie in a low dimensional subspace but allows the tasks in different groups to overlap with each other in one or more bases.
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
- Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé, Miroslav Dudík, H. Wallach
- Computer ScienceInternational Conference on Human Factors in…
- 13 December 2018
This first systematic investigation of commercial product teams' challenges and needs for support in developing fairer ML systems identifies areas of alignment and disconnect between the challenges faced by teams in practice and the solutions proposed in the fair ML research literature.
Incorporating Lexical Priors into Topic Models
- Jagadeesh Jagarlamudi, Hal Daumé, Raghavendra Udupa
- Computer ScienceConference of the European Chapter of the…
- 23 April 2012
This work proposes a simple and effective way to guide topic models to learn topics of specific interest to a user by providing sets of seed words that a user believes are representative of the underlying topics in a corpus.
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