'Source domain' presentation slideshows

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4 ? 5 ? Given by: ??????????????????. ?????. ?? ?? ???? ??. What is Cognition?. Mental processes, information processing Mental process or faculty of knowing, including awareness, perception, reasoning, and judgment. Cognitive Linguistics. Cognition is the way we think .

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System Overview

System Overview. Learning Two Senses of PUSH. Model merging based on Bayesian MDL. Training Results David Bailey. English 165 Training Examples, 18 verbs Learns optimal number of word senses (21) 32 Test examples : 78% recognition, 81% action All mistakes were close lift ~ yank , etc.

770 views • 67 slides

The Neural Basis of Thought and Language

655 views • 53 slides

Unsupervised and Transfer Learning Challenge

IJCNN 2011 San Jose, California Jul. 31, Aug. 5, 2011. Unsupervised and Transfer Learning Challenge. Isabelle Guyon Clopinet, California. Credits. Data donors:

569 views • 48 slides

A Survey on Transfer Learning

A Survey on Transfer Learning. Sinno Jialin Pan Department of Computer Science and Engineering The Hong Kong University of Science and Technology Joint work with Prof. Qiang Yang. Transfer Learning? (DARPA 05). Transfer Learning (TL):

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A Survey on Transfer Learning

A Survey on Transfer Learning. Sinno Jialin Pan Department of Computer Science and Engineering The Hong Kong University of Science and Technology Joint work with Prof. Qiang Yang. Transfer Learning? (DARPA 05). Transfer Learning (TL):

1k views • 42 slides

Exploiting domain and task regularities for robust named entity recognition

Exploiting domain and task regularities for robust named entity recognition. Ph.D. thesis proposal Andrew O. Arnold Machine Learning Department Carnegie Mellon University December 5, 2008 Thesis committee: William W. Cohen (CMU), Chair Tom M. Mitchell (CMU) Noah A. Smith (CMU)

428 views • 42 slides

Self-negotiation in Metaphor Construction and Interpretation ????????????

Self-negotiation in Metaphor Construction and Interpretation ???????????? . ??? Ningbo University . I. Metaphor. ? Traditional view:

550 views • 33 slides

Module 2

561 views • 30 slides

Knowledge as Love

Knowledge as Love. How Metaphors Direct our Efforts to Manage Knowledge in Organisations Keynote address 8th European Conference on Knowledge Management Consorci Escola Industrial de Barcelona (CEIB), Barcelona, Spain 6-7 September 2007

449 views • 30 slides

ACL(+WS) 2007 EMNLP- CoNLL 2007 ????

595 views • 29 slides

ACL(+WS) 2007 EMNLP-CoNLL 2007 ????

384 views • 28 slides

Improving the space-domain methods of forward modelling for geodynamic studies by GRACE

Improving the space-domain methods of forward modelling for geodynamic studies by GRACE. by Gabriel Strykowski, Danish National Space Center. Contents Motivation Theory Results Conclusions. Motivation

375 views • 28 slides

End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification

End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification. Zheng Li , Yu Zhang, Ying Wei, Yuxiang Wu, Qiang Yang Hong Kong University of Science and Technology. Overview. Problem & Related Work Motivation End-to-End Adversarial Memory Network Experiment

295 views • 28 slides

Cross-Domain Bootstrapping for Named Entity Recognition

NYU. Cross-Domain Bootstrapping for Named Entity Recognition . Ang Sun Ralph Grishman New York University July 28, 2011 Beijing, EOS, SIGIR 2011. NYU. Outline. Named Entity Recognition (NER) Domain Adaptation Problem for NER Cross-domain Bootstrapping

418 views • 20 slides

Cross-Domain Bootstrapping for Named Entity Recognition

NYU. Cross-Domain Bootstrapping for Named Entity Recognition. Ang Sun Ralph Grishman New York University July 28, 2011 Beijing, EOS, SIGIR 2011. NYU. Outline. Named Entity Recognition (NER) Domain Adaptation Problem for NER Cross-domain Bootstrapping

270 views • 20 slides

Lexical databases as resources for linguistic creativity: Focus on metaphor

368 views • 19 slides

e-mail: claudio.persello@disi.unitn.it, lorenzo.bruzzone@ing.unitn.it,

A NOVEL ACTIVE LEARNING STRATEGY FOR DOMAIN ADAPTATION IN THE CLASSIFICATION OF REMOTE SENSING IMAGES. C. Persello L. Bruzzone. e-mail: claudio.persello@disi.unitn.it, lorenzo.bruzzone@ing.unitn.it, Web page: http://rslab.disi.unitn.it. Outline.

155 views • 15 slides

Co-translator for Heterogeneous T ransfer L earning

Co-translator for Heterogeneous T ransfer L earning. Problem. Input n images with k labeled instances , k << n. (target domain) A set of English documents ; (source domain) Or a set of audio data . (source domain) Output Image classification function

201 views • 10 slides

Frustratingly Easy Domain Adaptation

Frustratingly Easy Domain Adaptation. Hal Daume III. Introduction. Task: Developing Learning Algorithms that can be easily ported from one domain to another. Example: from newswire to biomedical docs. particularly interesting in NLP.

198 views • 6 slides