This paper examines the application of linear transformations for speaker and environmental adaptation in an HMM-based speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias, strict linear feature-space transformations are inappropriate in this case. Hence, only model-b...

In recent years, there has been studies on the cardinality constrained multi-cycle problems on directed graphs, some of which considered chains co-existing on the same digraph whilst others did not. These studies were inspired by the optimal matching of kidneys known as the Kidney Exchange Problem (KEP). In a KEP, a vertex on the digraph represents a donor-patient pair who are related, though t...

Proving quantitative properties of programs, such as bounds on resource usage or information leakage, often leads to verification conditions that involve cardinalities of sets. Existing approaches for dealing with such verification conditions operate by checking cardinality bounds for given formulas. However, they cannot synthesize formulas that satisfy given cardinality constraints, which limi...

In portfolio theory, it is well-known that the distributions of stock returns often have non-Gaussian characteristics. Therefore, we need non-symmetric distributions for modeling and accurate analysis of actuarial data. For this purpose and optimal portfolio selection, we use the Tail Mean-Variance (TMV) model, which focuses on the rare risks but high losses and usually happens in the tail of r...

Decision makers are often described as seeking higher expected payo¤s and avoiding higher variance in payo¤s. We provide some necessary and some su¢ cient conditions for learning rules, that assume the agent has little prior and feedback information about the environment, to re‡ect such preferences. We adopt the framework of Börgers, Morales and Sarin (2004, Econometrica) who provide similar re...

In this work, we study constrained clustering, where some constraints are utilized to guide the clustering process. In existing work on this topic, two main categories of constraints have been explored, namely pairwise and cardinality constraints. Pairwise constraints enforce that the cluster labels of two instances be the same (must-link constraints) or different (cannot-link constraints). Car...

We consider maximizing a monotone submodular function under cardinality constraint or knapsack in the streaming setting. In particular, elements arrive sequentially and at any point of time, algorithm has access to only small fraction data stored primary memory. propose following algorithms taking O(ε− 1) passes: (1) (1 − e− 1 ε)-approximation for cardinality-constrained problem, (2) (0.5 knaps...