Fraud and Enforceability: Potential Implications for Federal Circuit Litigation

Should fraudulent litigation tactics and testimony affect the validity of underlying patents? What results are possible if the enforceability of a patent turns on the conduct of the applying party not only before the Patent and Trademark Office, but also before circuit courts? The author of the following article considers these questions in light of the recent Aptix Corp. case

Fraud and Enforceability: Potential Implications for Federal Circuit Litigation

Should fraudulent litigation tactics and testimony affect the validity of underlying patents? What results are possible if the enforceability of a patent turns on the conduct of the applying party not only before the Patent and Trademark Office, but also before circuit courts? The author of the following article considers these questions in light of the recent Aptix Corp. case

Towards Language-Universal End-to-End Speech Recognition

Building speech recognizers in multiple languages typically involves replicating a monolingual training recipe for each language, or utilizing a multi-task learning approach where models for different languages have separate output labels but share some internal parameters. In this work, we exploit recent progress in end-to-end speech recognition to create a single multilingual speech recognition system capable of recognizing any of the languages seen in training. To do so, we propose the use of a universal character set that is shared among all languages. We also create a language-specific gating mechanism within the network that can modulate the network's internal representations in a language-specific way. We evaluate our proposed approach on the Microsoft Cortana task across three languages and show that our system outperforms both the individual monolingual systems and systems built with a multi-task learning approach. We also show that this model can be used to initialize a monolingual speech recognizer, and can be used to create a bilingual model for use in code-switching scenarios.Comment: submitted to ICASSP 201

Order thresholding

A new thresholding method, based on L-statistics and called order thresholding, is proposed as a technique for improving the power when testing against high-dimensional alternatives. The new method allows great flexibility in the choice of the threshold parameter. This results in improved power over the soft and hard thresholding methods. Moreover, order thresholding is not restricted to the normal distribution. An extension of the basic order threshold statistic to high-dimensional ANOVA is presented. The performance of the basic order threshold statistic and its extension is evaluated with extensive simulations.Comment: Published in at http://dx.doi.org/10.1214/09-AOS782 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Impact of the allowance allocation on prices and efficiency

Successful cap and trade programs for SO2 and NOx in the US allocate allowances to large emitters based on a historic base line for a period of up to thirty years. National Allocation Plans in Europe allocate CO2 allowances in an iterative approach first for a three then for a five-year period. The potential updating of the base line creates perverse incentives for operation and investment. Some allowances are also reserved for new entrants further distorting the scheme. We use analytic models and numeric simulations for the UK power sector to illustrate and quantify how these effects contribute to an inflation of the allowance price while reducing utilisation and investment in efficient technologies. The inflated allowance prices are likely to increase the European allowance budget and emissions, e.g. through the Linking Directive. As a result opportunity costs of emitting CO2 are reduced relative to an efficient cap and trade program