Statistical and Computational Tradeoffs in Stochastic Composite Likelihood

Maximum likelihood estimators are often of limited practical use due to the intensive computation they require. We propose a family of alternative estimators that maximize a stochastic variation of the composite likelihood function. Each of the estimators resolve the computation-accuracy tradeoff differently, and taken together they span a continuous spectrum of computation-accuracy tradeoff resolutions. We prove the consistency of the estimators, provide formulas for their asymptotic variance, statistical robustness, and computational complexity. We discuss experimental results in the context of Boltzmann machines and conditional random fields. The theoretical and experimental studies demonstrate the effectiveness of the estimators when the computational resources are insufficient. They also demonstrate that in some cases reduced computational complexity is associated with robustness thereby increasing statistical accuracy.Comment: 30 pages, 97 figures, 2 author

Asymptotic Analysis of Generative Semi-Supervised Learning

Semisupervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likelihood we quantify the asymptotic accuracy of generative semi-supervised learning. In doing so, we complement distribution-free analysis by providing an alternative framework to measure the value associated with different labeling policies and resolve the fundamental question of how much data to label and in what manner. We demonstrate our approach with both simulation studies and real world experiments using naive Bayes for text classification and MRFs and CRFs for structured prediction in NLP.Comment: 12 pages, 9 figure

What Are Over-the-Road Truckers Paid For? Evidence from an Exogenous Regulatory Change on the Role of Social Comparisons and Work Organization in Wage Determination

Using evidence from recent work on truckers and disaggregated older data prior researchers did not have, we revisit a classic topic and find some new answers. We focus on differentials in average annual earnings at the firm level among mileage-paid over-the-road tractor-trailer drivers ("road drivers") employed by US for-hire trucking companies, before and after economic deregulation. Road driver output is individualized, and pay is on the basis of a piece rate (mileage). However, road drivers work under two distinct logistical systems – less-than-truckload [LTL], and truckload [TL] – associated with two different forms of work organization. We find that – contrary to the predictions of Rose (1987) – not only are road drivers for LTL companies paid more than those for TL companies, but in LTL the union earnings premium was maintained following deregulation and union coverage fell slowly, while in TL both the union differential and union coverage fell sharply. We review relevant theoretical explanations: payment for cognitive abilities or non-pecuniary disamenities; standard efficiency wage models based on independent utilities; sharing of product market rents; equity concerns resulting from social comparisons between employee groups; and differences in work organization as a source of union rents or quasi-rents. Only equity concerns, for the LTL earnings differential, and quasi rents (but not a union threat effect, contrary to Henrickson and Wilson (2008)), for union coverage and premium in LTL, are consistent with our empirical results. Both earnings differentials are based on differences in work organization, rather than differences in the workers or the work itself.less-than-truckload (LTL), trucker, trucking, work organization, rent-sharing, quasi-rent, cognitive ability, compensating differential, equity, fair wage, truckload (TL), regulation, deregulation, union premium

Next-to-Leading Order Shear Viscosity in lambda phi^4 Theory

We show that the shear viscosity of lambda phi^4 theory is sensitive at next-to-leading order to soft physics, which gives rise to subleading corrections suppressed by only a half power of the coupling, eta = [3033.54 + 1548.3 m_{th}/T] N T^3]/[ (N+2)/3 lambda^2], with m^2_th=(N+2)/72 lambda T^2. The series appears to converge about as well (or badly) as the series for the pressure.Comment: 4 pages, 1 figure. Typos fixed, tiny change in discussio

KQQKQQ and the Kasparov-World Game

The 1999 Kasparov-World game for the first time enabled anyone to join a team playing against a World Chess Champion via the web. It included a surprise in the opening, complex middle-game strategy and a deep ending. As the game headed for its mysterious finale, the World Team re-quested a KQQKQQ endgame table and was provided with two by the authors. This paper describes their work, compares the methods used, examines the issues raised and summarises the concepts involved for the benefit of future workers in the endgame field. It also notes the contribution of this endgame to chess itself

Space-efficient indexing of endgame tables for chess

Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame’s positions is crucial to meeting this objective. This paper updates Heinz’ previous review of approaches to indexing and describes the latest approach by the first and third authors. Heinz’ and Nalimov’s endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov’s EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 109 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs