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Algorithmic Bidding for Virtual Trading in Electricity MarketsFeb 08 2018Jul 31 2018We consider the problem of optimal bidding for virtual trading in two-settlement electricity markets. A virtual trader aims to arbitrage on the differences between day-ahead and real-time market prices; both prices, however, are random and unknown to ... More

Algorithmic Bidding for Virtual Trading in Electricity MarketsFeb 08 2018We consider the problem of optimal bidding for virtual trading in two-settlement electricity markets. A virtual trader aims to arbitrage on the differences between day-ahead and real-time market prices; both prices, however, are random and unknown to ... More

Online Learning and Optimization of Markov Jump Affine ModelsMay 07 2016The problem of online learning and optimization of unknown Markov jump affine models is considered. An online learning policy, referred to as Markovian simultaneous perturbations stochastic approximation (MSPSA), is proposed for two different optimization ... More

Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity AuctionsMar 07 2017Nov 17 2017We study the online learning problem of a bidder who participates in repeated auctions. With the goal of maximizing his T-period payoff, the bidder determines the optimal allocation of his budget among his bids for $K$ goods at each period. As a bidding ... More

Nonlinear Ionic Conductivity of Thin Solid Electrolyte Samples: Comparison between Theory and ExperimentMar 02 2005Nonlinear conductivity effects are studied experimentally and theoretically for thin samples of disordered ionic conductors. Following previous work in this field the {\it experimental nonlinear conductivity} of sodium ion conducting glasses is analyzed ... More

Harmonic analysis on directed graphs and applications: from Fourier analysis to waveletsNov 28 2018Feb 15 2019We introduce a novel harmonic analysis for functions defined on the vertices of a strongly connected directed graph of which the random walk operator is the cornerstone. As a first step, we consider the set of eigenvectors of the random walk operator ... More

The Asymptotic Performance of Linear Echo State Neural NetworksMar 25 2016In this article, a study of the mean-square error (MSE) performance of linear echo-state neural networks is performed, both for training and testing tasks. Considering the realistic setting of noise present at the network nodes, we derive deterministic ... More

Nanoscopic Study of the Ion Dynamics in a LiAlSiO$_4$ Glass Ceramic by means of Electrostatic Force SpectroscopyDec 08 2004We use time-domain electrostatic force spectroscopy (TD-EFS) for characterising the dynamics of mobile ions in a partially crystallised LiAlSiO$_4$ glass ceramic, and we compare the results of the TD-EFS measurements to macroscopic electrical conductivity ... More

Determining interface dielectric losses in superconducting coplanar waveguide resonatorsAug 30 2018Superconducting quantum computing architectures comprise resonators and qubits that experience energy loss due to two-level systems (TLS) in bulk and interfacial dielectrics. Understanding these losses is critical to improving performance in superconducting ... More

Analysis and mitigation of interface losses in trenched superconducting coplanar waveguide resonatorsSep 28 2017Improving the performance of superconducting qubits and resonators generally results from a combination of materials and fabrication process improvements and design modifications that reduce device sensitivity to residual losses. One instance of this ... More