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Predictive labeling

by Nao Hirokawa, Aart Middeldorp - In Proc. of RTA’06
"... Abstract. Semantic labeling is a transformation technique for proving the termination of rewrite systems. The semantic part is given by a quasi-model of the rewrite rules. In this paper we present a variant of semantic labeling in which the quasi-model condition is only demanded for the usable rules ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
Abstract. Semantic labeling is a transformation technique for proving the termination of rewrite systems. The semantic part is given by a quasi-model of the rewrite rules. In this paper we present a variant of semantic labeling in which the quasi-model condition is only demanded for the usable

Combining labeled and unlabeled data with co-training

by Avrim Blum, Tom Mitchell , 1998
"... We consider the problem of using a large unlabeled sample to boost performance of a learning algorithm when only a small set of labeled examples is available. In particular, we consider a setting in which the description of each example can be partitioned into two distinct views, motivated by the ta ..."
Abstract - Cited by 1633 (28 self) - Add to MetaCart
algorithm's predictions on new unlabeled examples are used to enlarge the training set of the other. Our goal in this paper is to provide a PAC-style analysis for this setting, and, more broadly, a PAC-style framework for the general problem of learning from both labeled and unlabeled data. We also

Predictive reward signal of dopamine neurons

by Wolfram Schultz - Journal of Neurophysiology , 1998
"... Schultz, Wolfram. Predictive reward signal of dopamine neurons. is called rewards, which elicit and reinforce approach behav-J. Neurophysiol. 80: 1–27, 1998. The effects of lesions, receptor ior. The functions of rewards were developed further during blocking, electrical self-stimulation, and drugs ..."
Abstract - Cited by 747 (12 self) - Add to MetaCart
conditions. that resemble reward-predicting stimuli or are novel or particularly Rewards come in various physical forms, are highly variable salient. However, only few phasic activations follow aversive stim-in time and depend on the particular environment of the subject. uli. Thus dopamine neurons label

Improved Boosting Algorithms Using Confidence-rated Predictions

by Robert E. Schapire , Yoram Singer - MACHINE LEARNING , 1999
"... We describe several improvements to Freund and Schapire’s AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each of their predictions. We give a simplified analysis of AdaBoost in this setting, and we show how this analysis can be used to find impr ..."
Abstract - Cited by 940 (26 self) - Add to MetaCart
We describe several improvements to Freund and Schapire’s AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each of their predictions. We give a simplified analysis of AdaBoost in this setting, and we show how this analysis can be used to find

Are investors reluctant to realize their losses

by Terrance Odean - Journal of Finance , 1998
"... I test the disposition effect, the tendency of investors to hold losing investments too long and sell winning investments too soon, by analyzing trading records for 10,000 accounts at a large discount brokerage house. These investors demonstrate a strong preference for realizing winners rather than ..."
Abstract - Cited by 657 (14 self) - Add to MetaCart
-motivated selling is most evident in December. THE TENDENCY TO HOLD LOSERS too long and sell winners too soon has been labeled the disposition effect by Shefrin and Statman ~1985!. For taxable investments the disposition effect predicts that people will behave quite differently than they would if they paid

Unrealistic optimism about future life events.

by Neil D Weinstein - Journal of Personality and Social Psychology, , 1980
"... Two studies investigated the tendency of people to be unrealistically optimistic about future life events. In Study 1, 258 college students estimated how much their own chances of experiencing 42 events differed from the chances of their classmates. Overall, they rated their own chances to be above ..."
Abstract - Cited by 535 (0 self) - Add to MetaCart
to be above average for positive events and below average for negative events, ps<.001. Cognitive and motivational considerations led to predictions that degree of desirability, perceived probability, personal experience, perceived controllability, and stereotype salience would influence the amount

A framework for learning predictive structures from multiple tasks and unlabeled data

by Rie Kubota Ando, Tong Zhang - JOURNAL OF MACHINE LEARNING RESEARCH , 2005
"... One of the most important issues in machine learning is whether one can improve the performance of a supervised learning algorithm by including unlabeled data. Methods that use both labeled and unlabeled data are generally referred to as semi-supervised learning. Although a number of such methods ar ..."
Abstract - Cited by 443 (3 self) - Add to MetaCart
One of the most important issues in machine learning is whether one can improve the performance of a supervised learning algorithm by including unlabeled data. Methods that use both labeled and unlabeled data are generally referred to as semi-supervised learning. Although a number of such methods

Predictive labeling with dependency pairs using SAT

by Adam Koprowski, Aart Middeldorp - in: Proc. 21st CADE, LNAI 4603, 2007
"... Abstract. This paper combines predictive labeling with dependency pairs and reports on its implementation. Our starting point is the method of proving termination of rewrite systems using semantic labeling with infinite models in combination with lexicographic path orders. We replace semantic labeli ..."
Abstract - Cited by 7 (4 self) - Add to MetaCart
Abstract. This paper combines predictive labeling with dependency pairs and reports on its implementation. Our starting point is the method of proving termination of rewrite systems using semantic labeling with infinite models in combination with lexicographic path orders. We replace semantic

An information flow model for conflict and fission in small groups

by Wayne W. Zachary - J. Anthropolog. Res , 1977
"... Data from a voluntary association are used to construct a new formal model for a traditional anthropological problem, fission in small groups. The process leading to fission is viewed as an unequal flow of sentiments and information across the ties in a social network. This flow is unequal because i ..."
Abstract - Cited by 380 (0 self) - Add to MetaCart
it is uniquely constrained by the contextual range and sensitivity of each relationship in the network. The subsequent differential sharing of sentiments leads to the formation of subgroups with more internal stability than the group as a whole, and results in fission. The Ford-Fulkerson labeling algorithm

Evaluating Interval Forecasts

by Peter F. Christoffersen, Anil Bera, Jeremy Berkowitz, Tim Bollerslev, Frank Diebold, Lorenzo Giorgianni, Jin Hahn, Jose Lopez, Roberto Mariano - International Economic Review , 1997
"... This paper is intended to address the deficiency by clearly defining what is meant by a "good" interval forecast, and describing how to test if a given interval forecast deserves the label "good". One of the motivations of Engle's (1982) classic paper was to form dynamic int ..."
Abstract - Cited by 364 (11 self) - Add to MetaCart
This paper is intended to address the deficiency by clearly defining what is meant by a "good" interval forecast, and describing how to test if a given interval forecast deserves the label "good". One of the motivations of Engle's (1982) classic paper was to form dynamic
Results 1 - 10 of 4,685