27656613
Multi-level Loop Fusion with Minimal Code Size
17091320
Universal routing in distributed networks
We show that universal routing can be achieved with low overhead in distributed networks. The validity of our results rests on a new network called the fat-stack. We show that from a routing perspective the fat-stack is efficient and is suitable for use as a baseline distributed network We prove that the fat-stack is universal by routing efficiency. A requirement for the fat-stack to be universal is that link capacities double up the levels of the network. We use methods developed in the areas of VLSI and processor interconnect for much of our analysis. Our universality proof shows that a fat-stack of area /spl Theta/(A) can simulate any competing network of area A with O(log/sup 3/2/ A) overhead independently of wire delay. The universality result implies that the fat-stack of a given size is nearly the best routing network of that size. The fat-stack is also the minimal universal network for an O(log/sup 3/2/ A) overhead in terms of number of links.
2853176
Loop Fusion via Retiming for DSP Applications
32262987
Speaker Modeling with Various Speech Representations
Although numerous speech representations have been reported to be useful in speaker recognition, there is much less agreement on which speech representation provides a perfect representation of speaker-specific information. In this paper, we charaterize a speaker’s identity through the simultaneous use of various speech representations of his/her voice. We present a parametric statistical model, generalized Gaussian mixture model, and develop an EM algorithm for parameter estimation. Our approach has been applied to speaker recognition and comparative results on KING corpus demonstrate its effectiveness.
4677399
Transitive Signatures Based on Bilinear Maps
The notion of transitive signature, firstly introduced by Micali and Rivest, is a way to digitally sign the vertices and edges of a dynamically growing, transitively closed graph. All the previous proposed transitive signature schemes were constructed from discrete logarithm, factoring, or RSA assumption. In this paper, we introduce two alternative realizations of transitive signature based on bilinear maps. The proposed transitive signature schemes possess the following properties: (i) they are provably secure against adaptive chosen-message attacks in the random oracle model; (ii) there are no need for node certificates in our transitive signature schemes, so the signature algebra is compact; (iii) if using Weil pairing, our signature schemes are more efficient than all previous proposed schemes.
378309
Type-directed weaving of aspects for higher-order functional languages
Aspect-oriented programming (AOP) has been shown to be a useful model for software development. Special care must be taken when we try to adapt AOP to strongly typed functional languages which come with features like a type inference mechanism, polymorphic types, higher-order functions and type-scoped pointcuts. Our main contribution lies in a seamless integration of these two paradigms through a static weaving process which deals with around advices with type-scoped pointcuts in the presence of higher-order functions. We give a source-level type inference system for a higher-order, polymorphic language coupled with type-scoped pointcuts. The type system ensures that base programs are oblivious to the type of around advices. We present a type-directed translation scheme which resolves all advice applications at static time. The translation removes advice declarations from source programs and produces translated code which is typable in the Hindley-Milner system.
15289343
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a modular neural network architecture is proposed through use of soft competition among diverse features. Parameter estimation in the proposed architecture is treated as a maximum likelihood problem, and an Expectation-Maximization (EM) learning algorithm is developed for adjusting the parameters of the architecture. Comparative simulation results are presented for the real world problem of speaker identification.
3162448
A Space-Efficient Randomized DNA Algorithm for k-SAT
We present a randomized DNA algorithm for k-SAT based on the classical algorithm of Paturi et al. [8]. For an n-variable, m-clause instance of k-SAT (m > n), our algorithm finds a satisfying assignment, assuming one exists, with probability 1-e-α, in worst-case time O(k2mn) and space O(2(1-1/k)n+log α). This makes it the most space-efficient DNA k-SAT algorithm for k > 3 and k < n=log α (i.e. the clause size is small compared to the number of variables). In addition, our algorithm is the first DNA algorithm to adapt techniques from the field of randomized classical algorithms.