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Stability properties of empirical risk minimization over Donsker classes
 Journal of Machine Learning Research. Accepted. Available at http://cbcl.mit.edu/people/rakhlin/erm.pdf
, 2006
"... We study some stability properties of algorithms which minimize (or almostminimize) empirical error over Donsker classes of functions. We show that, as the number n of samples grows, the L2diameter of the set of almostminimizers of empirical error with tolerance ξ(n) = o(n − 1 2) converges to zer ..."
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Cited by 6 (0 self)
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We study some stability properties of algorithms which minimize (or almostminimize) empirical error over Donsker classes of functions. We show that, as the number n of samples grows, the L2diameter of the set of almostminimizers of empirical error with tolerance ξ(n) = o(n − 1 2) converges
Risk, Return and Equilibrium: Empirical Tests
 Journal of Political Economy
, 1973
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
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Cited by 1445 (10 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Some properties of empirical risk minimization over donsker classes
 AI Memo 2005018, Massachusetts Institute of Technology
, 2005
"... Abstract. We study properties of algorithms which minimize (or almostminimize) empirical error over a Donsker class of functions. We show that the L2diameter of the set of almostminimizers is converging to zero in probability. Therefore, as the number of samples grows, it is becoming unlikely tha ..."
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Cited by 4 (3 self)
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Abstract. We study properties of algorithms which minimize (or almostminimize) empirical error over a Donsker class of functions. We show that the L2diameter of the set of almostminimizers is converging to zero in probability. Therefore, as the number of samples grows, it is becoming unlikely
Powerlaw distributions in empirical data
 ISSN 00361445. doi: 10.1137/ 070710111. URL http://dx.doi.org/10.1137/070710111
, 2009
"... Powerlaw distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and manmade phenomena. Unfortunately, the empirical detection and characterization of power laws is made difficult by the large fluctuations that occur in the t ..."
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Cited by 589 (7 self)
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Powerlaw distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and manmade phenomena. Unfortunately, the empirical detection and characterization of power laws is made difficult by the large fluctuations that occur
Empirical performance of alternative option pricing models
 Journal of Finance
, 1997
"... reserved. Readers may make verbatim copies of this document for noncommercial purposes by any means, provided that this copyright notice appears on all such copies. ..."
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Cited by 676 (18 self)
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reserved. Readers may make verbatim copies of this document for noncommercial purposes by any means, provided that this copyright notice appears on all such copies.
The 2005 pascal visual object classes challenge
, 2006
"... Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not presegmented objects). Four object classes were selected: motorbikes, bicycles, cars and peop ..."
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Cited by 633 (24 self)
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Abstract. The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not presegmented objects). Four object classes were selected: motorbikes, bicycles, cars
Noise Trader Risk in Financial Markets
 Jolurnial of Political Economy
, 1990
"... We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders ’ beliefs creates a risk in the price of the asset that deters rational ..."
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Cited by 858 (23 self)
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We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders ’ beliefs creates a risk in the price of the asset that deters rational
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
 MACHINE LEARNING
, 1999
"... Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and realworld datasets. We review these algorithms and describe a large empirical study comparing several variants in co ..."
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Cited by 695 (2 self)
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Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and realworld datasets. We review these algorithms and describe a large empirical study comparing several variants
For Most Large Underdetermined Systems of Linear Equations the Minimal ℓ1norm Solution is also the Sparsest Solution
 Comm. Pure Appl. Math
, 2004
"... We consider linear equations y = Φα where y is a given vector in R n, Φ is a given n by m matrix with n < m ≤ An, and we wish to solve for α ∈ R m. We suppose that the columns of Φ are normalized to unit ℓ 2 norm 1 and we place uniform measure on such Φ. We prove the existence of ρ = ρ(A) so that ..."
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Cited by 560 (10 self)
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that for large n, and for all Φ’s except a negligible fraction, the following property holds: For every y having a representation y = Φα0 by a coefficient vector α0 ∈ R m with fewer than ρ · n nonzeros, the solution α1 of the ℓ 1 minimization problem min �x�1 subject to Φα = y is unique and equal to α0
Liquidity Risk and Expected Stock Returns
, 2002
"... This study investigates whether marketwide liquidity is a state variable important for asset pricing. We find that expected stock returns are related crosssectionally to the sensitivities of returns to fluctuations in aggregate liquidity. Our monthly liquidity measure, an average of individualsto ..."
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Cited by 590 (4 self)
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stock measures estimated with daily data, relies on the principle that order flow induces greater return reversals when liquidity is lower. Over a 34year period, the average return on stocks with high sensitivities to liquidity exceeds that for stocks with low sensitivities by 7.5 % annually, adjusted
Results 1  10
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302,813