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Currently our world is becoming increasingly urban, with around 50% of its population living in cities. Whereas cities produce 80% of the worldwide GDP and are places with high innovation, they also consume 75% of worldwide resources and produce 80% of CO2 ...
In our HST photometric survey, we have been searching for multiple stellar populations (MPs) in Magellanic Clouds (MCs) massive star clusters which span a significant range of ages (similar to 1.5-11Gyr). In the previous papers of the series, we have shown ...
Clusters and nanocrystals constitute intermediates between molecules and condensed matter. Due to their finite size, clusters have a wide spectrum of applications ranging from building blocks for novel materials to model systems for fundamental investigati ...
Covariance operators play a fundamental role in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen-Loève expansion. These operators may themselves be subject to variation, for instance in con ...
This paper considers optimization problems over networks where agents have individual objectives to meet, or individual parameter vectors to estimate, subject to subspace constraints that enforce the objectives across the network to lie in a low-dimensiona ...
Feature extraction is a key step in many machine learning and signal processing applications. For speech signals in particular, it is important to derive features that contain both the vocal characteristics of the speaker and the content of the speech. In ...
Power gating is a common approach for reducing circuit static power consumption. In FPGAs, resources that dominate static power consumption lie in the routing network. Researchers have proposed several heuristics for clustering multiplexers in the routing ...
Linear subspace models are pervasive in computational sciences and particularly used for large datasets which are often incomplete due to privacy issues or sampling constraints. Therefore, a critical problem is developing an efficient algorithm for detecti ...
The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personaliz ...
This thesis deals with exploiting the low-dimensional multi-subspace structure of speech towards the goal of improving acoustic modeling for automatic speech recognition (ASR). Leveraging the parsimonious hierarchical nature of speech, we hypothesize that ...
