priya venkateshan - user overview - MetaOptimize Q+A

priya venkateshan

164

karma

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member since	Aug 09 '10 at 00:56
last seen	Nov 16 '11 at 16:02

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6 Questions

1

votes

4

answers

971

views

Survey papers for coreference resolution?

Apr 27 '11 at 23:56 Yang Song1●1●2 (asked by priya venkateshan164●6●8●12 )

coreference-resolution survey

0

votes

1

answers

1k

views

Challenges in Coreference Resolution

Nov 13 '10 at 23:58 priya venkateshan164●6●8●12

nlp coreference-resolution machine-learning

3

votes

3

answers

1k

views

Adding noise to (text) data

Dec 06 '10 at 13:00 Dave Lewis785●16●26●44 (asked by priya venkateshan164●6●8●12 )

text noise data noisy

1

votes

1

answers

1k

views

Canonical correlation analysis and Transfer Learning

Jan 15 '11 at 02:16 spinxl393473●10●43●68 (asked by priya venkateshan164●6●8●12 )

feature-selection multi-task-learning transfer-learning canonical-component-analysis

-1

votes

1

answers

1k

views

Weka for Transfer Learning?

Aug 10 '10 at 07:31 spinxl393473●10●43●68 (asked by priya venkateshan164●6●8●12 )

weka transfer-learning

1

votes

2

answers

1k

views

Transfer learning on text data

Nov 10 '10 at 20:00 Robert Layton1520●10●23●37 (asked by priya venkateshan164●6●8●12 )

text-mining transfer-learning features

6 Answers

Best resource to learn about conditional random fields?

Normalized Google DIstance

Survey paper for Topic Models

In which domains is Transfer Learning useful?

Checking that my test/training datasets are from the same distribution

Difference between domain adaptation and multitask learning

4 Votes

4

0

25 Tags

transfer-learning × 10
coreference-resolution × 5
features × 5
text-mining × 5
survey × 5
noisy × 3
data × 3
text × 3
multi-task-learning × 3
noise × 3

canonical-component-analysis × 2
feature-selection × 2
weka × 2
machine-learning × 1
bayesian × 1
nlp × 1
semantic × 1
topic-models × 1
distributions × 1
crf × 1

training × 1
test × 1
references × 1
domain-adaptation × 1
similarity × 1

10 Kudos

● Conspicuous Question × 6
● Prominent Question × 6
● Well-Known Question × 6
● Prized Question × 2
● Appreciated Question × 1
● Advocate × 1

● Guide × 1
● Appreciated Answer × 1
● Inquisitive × 1
● Revisionist × 1

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