Incorporating Machine Learning into Established Bioinformatics Frameworks

The exponential growth of biomedical data in recent years has urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research. By enabling the automatic feature extraction, selection, and generation of predictive models, these methods can be used to efficiently study complex biological systems. Machine learning techniques are frequently integrated with bioinformatic methods, as well as curated databases and biological networks, to enhance training and validation, identify the best interpretable features, and enable feature and model investigation. Here, we review recently developed methods that incorporate machine learning within the same framework with techniques from molecular evolution, protein structure analysis, systems biology, and disease genomics. We outline the challenges posed for machine learning, and, in particular, deep learning in biomedicine, and suggest unique opportunities for machine learning techniques integrated with established bioinformatics approaches to overcome some of these challenges.     

RL \subseteq SC

We show that any randomized logspace algorithm (running in polynomial time with bounded two-sided error) can be simulated deterministically in polynomial time andO(log² n) space. This puts RL in SC, Steve's Class In particular, we get a polynomial time,O(log² n) space algorithm for thest-connectivity problem on undirected graphs.Subject classifications. 68Q10, 68Q15, 68Q25.     

Express Virtual Channels with Capacitively Driven Global Links

Networks on chip must deliver high bandwidth at low latencies while keeping within a tight power envelope. Using express virtual channels for flow control improves energy-delay throughput by letting packets bypass intermediate routers, but EVCs have key limitations. Nochi (NoC with hybrid interconnect) overcomes these limitations by transporting data payloads and control information on separate planes, optimized for bandwidth and latency respectively.     

Enhancing comparison shopping agents through ordering and gradual information disclosure

The plethora of comparison shopping agents (CSAs) in today’s markets enables buyers to query more than a single CSA when shopping, thus expanding the list of sellers whose prices they obtain. This potentially decreases the chance of a purchase within any single interaction between a buyer and a CSA, and consequently decreases each CSAs’ expected revenue per-query. Obviously, a CSA can improve its competence in such settings by acquiring more sellers’ prices, potentially resulting in a more attractive “best price”. In this paper we suggest a complementary approach that improves the attractiveness of the best result returned based on intelligently controlling the order according to which they are presented to the user, in a way that utilizes several known cognitive-biases of human buyers. The advantage of this approach is in its ability to affect the buyer’s tendency to terminate her search for a better price, hence avoid querying further CSAs, without spending valuable resources on finding additional prices to present. The effectiveness of our method is demonstrated using real data, collected from four CSAs for five products. Our experiments confirm that the suggested method effectively influence people in a way that is highly advantageous to the CSA compared to the common method for presenting the prices. Furthermore, we experimentally show that all of the components of our method are essential to its success.     

A theoretical framework and empirical examination of the effects of foreign and translated interface language

Given the increased globalization and popularization of computer applications, translating a system's human interface into the local language has become a major consideration for software vendors and distributors. In this paper, we suggest a theoretical framework for the study of user interface translation. The framework includes recognizing vendors' and users' costs of, and benefits from, software translation. An experiment was conducted, based on this framework, to test user performance and preferences regarding interface translations. The experiment manipulated the translation of two interface components: documentation language and manipulation language. The results indicate that users are sensitive to different combinations of interface translation in a way that is commensurate with the instruction-following process (Terwilliger and Polson 1997). Users performed best when a fully translated interface was used and worst when only the manipulation language was translated. Users' preferences were in line with their performance, indicating that a cost benefit approach can serve as a promising starting point to the study of interface translation.     

Competitive analysis of incentive compatible on-line auctions

This paper studies auctions in a setting where the different bidders arrive at different times and the auction mechanism is required to make decisions about each bid as it is received. Such settings occur in computerized auctions of computational resources as well as in other settings. We call such auctions, on-line auctions.

We first characterize exactly on-line auctions that are incentive compatible, i.e. where rational bidders are always motivated to bid their true valuation. We then embark on a competitive worst-case analysis of incentive compatible on-line auctions. We obtain several results, the cleanest of which is an incentive compatible on-line auction for a large number of identical items. This auction has an optimal competitive ratio, both in terms of seller's revenue and in terms of the total social efficiency obtained.     

Molecular Alignment Induced by Ultrashort Laser Pulses and Its Impact on Molecular Motion

Spectroscopy aims at extracting information about matter through its interaction with light. However, when performed on gas and liquid phases as well as solid phases lacking long-range order, the extracted spectroscopic features are in fact averaged over the molecular isotropic angular distributions. The reason is that light–matter processes depend on the angle between the transitional molecular dipole and the polarization of the light interacting with it. This understanding gave birth to the constantly expanding field of “laser-induced molecular alignment”. In this paper, we attempt to guide the readers through our involvement (both experimental and theoretical) in this field in the last few years. We start with the basic phenomenon of molecular alignment induced by a single pulse, continue with selective alignment of close molecular species and unidirectional molecular rotation induced by two time-delayed pulses, and lead up to novel schemes for manipulating the spatial distributions of molecular samples through rotationally controlled scattering off inhomogeneous fields and surfaces.     

Automatic negotiation: playing the domain instead of the opponent

An automated negotiator is an intelligent agent whose task is to reach the best possible agreement. We explore a novel approach to developing a negotiation strategy, a ‘domain-based approach’. Specifically, we use two domain parameters, reservation value and discount factor, to cluster the domain into different regions, in each of which we employ a heuristic strategy based on the notions of temporal flexibility and bargaining strength. Following the presentation of our cognitive and formal models, we show in an extensive experimental study that an agent based on that approach wins against the top agents of the automated negotiation competition of 2012 and 2013, and attained the second place in 2014.