Imagine the following situation. You’re in your car, listening to the radio and suddenly you hear a song that catches your attention. It’s the best new song you have heard for a long time, but you missed the announcement and don’t recognize the artist. Still, you would like to know more about

is probabilistic in nature, but as we show empirically and theoretically, it can find time series motifs with very high probability even in the presence of noise or “don’t care ” symbols. Not only is the algorithm fast, but it is an anytime algorithm, producing likely candidate motifs almost immediately

to consider only the significant terms in Eqs. [27] and [28] and restrict higher order fitting to border regions. RESULTS Sensitivity encoding using common Cartesian sampling of k-space and DFT-based reconstruction was performed in vitro and in vivo on a Philips Gyroscan ACS-NT15 at 1.5 T. Phantom

The main technique used in algorithm design for approximating #P-hard counting problems is the Markov chain Monte Carlo method. At the heart of the method is the study of the convergence (mixing) rates of particular Markov chains of interest. In this paper we illustrate a new approach

. In this work, we explore more aggressive 3D DRAM organizations that make better use of the additional die-to-die bandwidth provided by 3D stacking, as well as the additional transistor count. Our simulation results show that with a few simple changes to the 3D-DRAM organization, we can achieve a 1.75 × speedup

core meaning. An analysis is presented in which word senses are abstractions from clusters of corpus citations, in accordance with current lexicographic practice. The corpus citations, not the word senses, are the basic objects in the ontology. The corpus citations will be clustered into senses

In this paper, we present the Tiny Tera: a small packet switch with an aggregate bandwidth of 320Gb/s. The Tiny Tera is a CMOS-based input-queued, fixed-size packet switch suitable for a wide range of applications such as a highperformance ATM switch, the core of an Internet router or as a fast

Growing transistor counts, limited power budgets, and the breakdown of voltage scaling are currently conspiring to create a utilization wall that limits the fraction of a chip that can run at full speed at one time. In this regime, specialized, energy-efficient processors can increase parallelism

The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features

Abstract Context-predicting models (more commonly known as embeddings or neural language models) are the new kids on the distributional semantics block. Despite the buzz surrounding these models, the literature is still lacking a systematic comparison of the predictive models with classic, count