Chiral Boson Theory on the Light-Front

The {\it front form} framework for describing the quantized theory of chiral boson is discussed. It avoids the conflict with the requirement of the principle of microcausality as is found in the conventional equal- time treatment. The discussion of the Floreanini-Jackiw model and its modified version for describing the chiral boson becomes very transparent on the light-front.Comment: 9 pages, plain Late

Perspectives of Light-Front Quantized Field Theory: Some New Results

Some basic topics in the light-front (LF) quantization of relativistic field theory are reviewed. It is argued that the LF quantization is equally appropriate as the conventional one and that they lead, assuming the micro- causality principle, to the same physical content. This is confirmed in the studies on the LF of the spontaneous symmetry breaking (SSB), of the degenerate vacua in Schwinger model (SM) and Chiral SM (CSM), of the chiral boson theory, and of the QCD in covariant gauges among others. The discussion on the LF is more economical and more transparent. In the context of the Dyson-Wick pertur- bation theory the relevant popagators in the front form theory are causal. The Wick rotation can then be performed to employ the Euclidean space integrals in momentum space. The lack of manifest covariance becomes tractable, and still more so if we employ, as discussed in the text, the Fourier transform of the fermionic field based on a special construction of the LF spinor. The fact that the hyperplanes $x^{pm}=0$ constitute characteristic surfaces of the hyper- bolic partial differential equation is found irrelevant in the quantized theory.Comment: 50 pages, plain Latex, Invited article for "Saga of Field Theory: From Points to Strings", Eds., A.N. Mitra et al., Indian National Science Academy-INSA, Indi

On The Risk Of Unemployment: A Comparative Assessment of the Labour Market Success of Migrants in Australia

One important indicator of the successful assimilation of immigrants is the comparison of the relative success of immigrants and of the native born population in finding employment under different macro economic regimes that affect the overall rate of unemployment in an economy. This paper analyzes the "risk" of unemployment of male immigrants to Australia relative to the native born for two different time periods in which the overall labour market characteristics and the pool of immigrants differ considerably. The two data sets used are the 1990 Income and Housing Costs Survey conducted by the Australian Bureau of Statistics and the first wave of the Household Income and Labour Dynamics in Australia (HILDA) survey whose data refer primarily to the 2001 calendar year. The paper analyzes the correlates of unemployment at the individual level using logistic and probit regression models. It uses both a standard specification of the probability of being unemployed determined by individual and family level socio-economic characteristics (i.e. years of schooling and work experience, age, years since migration, etc.); and an extended model that is feasible only with the extra information available in the HILDA data set. The results show there is a clear disadvantage in the probability of finding employment for migrants with similar characteristics of a native born Australian in both the standard and extended model specifications. There also are very distinct country of birth effects which persist even after controlling for the individual migrant's English language skills. The relative disadvantage of migrants has not diminished between the two time periods in spite of greater emphasis on skilled migration in recent years. By providing a clearer understanding of why and how the individual and subgroup level characteristics are correlated with the probability of an individual being unemployed, this paper gives valuable insights on how the Australian labor market functions, and, in particular on how it evaluates the employment prospects of specific immigrant groups.employment prospects of migrants, immigrant workers and assimilation, unemployment probabilities, immigrants in Australia

A Batch Learning Framework for Scalable Personalized Ranking

In designing personalized ranking algorithms, it is desirable to encourage a high precision at the top of the ranked list. Existing methods either seek a smooth convex surrogate for a non-smooth ranking metric or directly modify updating procedures to encourage top accuracy. In this work we point out that these methods do not scale well to a large-scale setting, and this is partly due to the inaccurate pointwise or pairwise rank estimation. We propose a new framework for personalized ranking. It uses batch-based rank estimators and smooth rank-sensitive loss functions. This new batch learning framework leads to more stable and accurate rank approximations compared to previous work. Moreover, it enables explicit use of parallel computation to speed up training. We conduct empirical evaluation on three item recommendation tasks. Our method shows consistent accuracy improvements over state-of-the-art methods. Additionally, we observe time efficiency advantages when data scale increases.Comment: AAAI 2018, Feb 2-7, New Orleans, US