Conic Multi-Task Classification

Traditionally, Multi-task Learning (MTL) models optimize the average of task-related objective functions, which is an intuitive approach and which we will be referring to as Average MTL. However, a more general framework, referred to as Conic MTL, can be formulated by considering conic combinations of the objective functions instead; in this framework, Average MTL arises as a special case, when all combination coefficients equal 1. Although the advantage of Conic MTL over Average MTL has been shown experimentally in previous works, no theoretical justification has been provided to date. In this paper, we derive a generalization bound for the Conic MTL method, and demonstrate that the tightest bound is not necessarily achieved, when all combination coefficients equal 1; hence, Average MTL may not always be the optimal choice, and it is important to consider Conic MTL. As a byproduct of the generalization bound, it also theoretically explains the good experimental results of previous relevant works. Finally, we propose a new Conic MTL model, whose conic combination coefficients minimize the generalization bound, instead of choosing them heuristically as has been done in previous methods. The rationale and advantage of our model is demonstrated and verified via a series of experiments by comparing with several other methods.Comment: Accepted by European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD)-201

A chain rule for the expected suprema of Gaussian processes

The expected supremum of a Gaussian process indexed by the image of an index set under a function class is bounded in terms of separate properties of the index set and the function class. The bound is relevant to the estimation of nonlinear transformations or the analysis of learning algorithms whenever hypotheses are chosen from composite classes, as is the case for multi-layer models

Generation and evaluation of a large mutational library from the Escherichia coli mechanosensitive channel of large conductance, MscL - Implications for channel gating and evolutionary design

Random mutagenesis of the mechanosensitive channel of large conductance (MscL) from Escherichia coli coupled with a high-throughput functional screen has provided new insights into channel structure and function. Complementary interactions of conserved residues proposed in a computational model for gating have been evaluated, and important functional regions of the channel have been identified. Mutational analysis shows that the proposed S1 helix, despite having several highly conserved residues, can be heavily mutated without significantly altering channel function. The pattern of mutations that make MscL more difficult to gate suggests that MscL senses tension with residues located near the lipid headgroups of the bilayer. The range of phenotypical changes seen has implications for a proposed model for the evolutionary origin of mechanosensitive channels

Energy Efficient Service Delivery in Clouds in Compliance with the Kyoto Protocol

Cloud computing is revolutionizing the ICT landscape by providing scalable and efficient computing resources on demand. The ICT industry - especially data centers, are responsible for considerable amounts of CO2 emissions and will very soon be faced with legislative restrictions, such as the Kyoto protocol, defining caps at different organizational levels (country, industry branch etc.) A lot has been done around energy efficient data centers, yet there is very little work done in defining flexible models considering CO2. In this paper we present a first attempt of modeling data centers in compliance with the Kyoto protocol. We discuss a novel approach for trading credits for emission reductions across data centers to comply with their constraints. CO2 caps can be integrated with Service Level Agreements and juxtaposed to other computing commodities (e.g. computational power, storage), setting a foundation for implementing next-generation schedulers and pricing models that support Kyoto-compliant CO2 trading schemes

An Interview With Albert W. Tucker

The mathematical career of Albert W. Tucker, Professor Emeritus at Princeton University, spans more than 50 years. Best known today for his work in mathematical programming and the theory of games (e.g., the Kuhn-Tucker theorem, Tucker tableaux, and the Prisoner\u27s Dilemma), he was also in his earlier years prominent in topology. Outstanding teacher, administrator and leader, he has been President of the MAA, Chairman of the Princeton Mathematics Department, and course instructor, thesis advisor or general mentor to scores of active mathematicians. He is also known for his views on mathematics education and the proper interplay between teaching and research. Tucker took an active interest in this interview, helping with both the planning and the editing. The interviewer, Professor Maurer, received his Ph.D. under Tucker in 1972 and teaches at Swarthmore College

Development of strategies to improve quality and safety and reduce cost of production in organic and “low input” livestock production systems

The demand for organic livestock products is still increasing. To support this growth and to help remove potential obstacles the fourth Subproject of QLIF addresses several themes related to livestock farming. In this overview paper the main results to date are presented. It briefly discusses progress made on preventative treatments against pig and poultry parasites, as well as the reduction of rodent burdens on farm. The activities on probiotics and nutribiotics experiments are listed, as are studies undertaken to improve the meat quality of pigs through different protein sources and diet composition. Finally, work is being presented aiming to reduce the incidence of mastitis, and the reduction of faecal shedding of pathogens in cattle. The overview concludes that much work has been done, but that the main task of increasing competitiveness of the organic and low-input livestock sector through the implementation of our knowledge, still lies ahead of us

Development of new materials for turbopump bearings

The life requirement for the angular contact ball bearings in the Space Shuttle Main Engine (SSME) high pressure oxygen turbopump (HPOTP) is 7.5 hours. In actual operation, significantly shorter service life was experienced. The objective is to identify bearing materials and/or materials processing techniques offering signficant potential for extending HPOTP bearing performance life. Interactive thermomechanical analysis of the HPOTP bearing-shaft system was performed with the SHABERTH computer program. Bearing fatigue life, ball-race contact stress, heat generation rate, bulk ring temperatures and circumferential stress in the inner rings were quantified as functions of radial load, thrust load and ball-race contact friction. Criteria established from the output of this analysis are being used for material candidate selection

Safety management of a complex R and D ground operating system

A perspective on safety program management was developed for a complex R&D operating system, such as the NASA-Lewis Research Center. Using a systems approach, hazardous operations are subjected to third-party reviews by designated-area safety committees and are maintained under safety permit controls. To insure personnel alertness, emergency containment forces and employees are trained in dry-run emergency simulation exercises. The keys to real safety effectiveness are top management support and visibility of residual risks