Zobrazeno 1 - 10
of 9 074
pro vyhledávání: '"Pesenti, A."'
Autor:
Jones, Chris, Pesenti, Lucas
We study a general class of first-order iterative algorithms which includes power iteration, belief propagation and Approximate Message Passing (AMP), and many forms of gradient descent. When the input is a random matrix with i.i.d. entries, we prese
Externí odkaz:
http://arxiv.org/abs/2404.07881
Autor:
Pesenti, Silvana M., Vanduffel, Steven
We employ scoring functions, used in statistics for eliciting risk functionals, as cost functions in the Monge-Kantorovich (MK) optimal transport problem. This gives raise to a rich variety of novel asymmetric MK divergences, which subsume the family
Externí odkaz:
http://arxiv.org/abs/2311.12183
Differential sensitivity measures provide valuable tools for interpreting complex computational models used in applications ranging from simulation to algorithmic prediction. Taking the derivative of the model output in direction of a model parameter
Externí odkaz:
http://arxiv.org/abs/2310.06151
We give new rounding schemes for SDP relaxations for the problems of maximizing cubic polynomials over the unit sphere and the $n$-dimensional hypercube. In both cases, the resulting algorithms yield a $O(\sqrt{n/k})$ multiplicative approximation in
Externí odkaz:
http://arxiv.org/abs/2310.00393
We introduce a framework for quantifying propagation of uncertainty arising in a dynamic setting. Specifically, we define dynamic uncertainty sets designed explicitly for discrete stochastic processes over a finite time horizon. These dynamic uncerta
Externí odkaz:
http://arxiv.org/abs/2308.12856
We study a reinsurer who faces multiple sources of model uncertainty. The reinsurer offers contracts to $n$ insurers whose claims follow compound Poisson processes representing both idiosyncratic and systemic sources of loss. As the reinsurer is unce
Externí odkaz:
http://arxiv.org/abs/2308.11828
We consider a problem where autonomous agents enter a dynamic and unknown environment described by a network of weighted arcs. These agents move within the network from node to node according to a decentralized policy using only local information, wi
Externí odkaz:
http://arxiv.org/abs/2306.07139
We define and develop an approach for risk budgeting allocation -- a risk diversification portfolio strategy -- where risk is measured using a dynamic time-consistent risk measure. For this, we introduce a notion of dynamic risk contributions that ge
Externí odkaz:
http://arxiv.org/abs/2305.11319
Risk budgeting is a portfolio strategy where each asset contributes a prespecified amount to the aggregate risk of the portfolio. In this work, we propose an efficient numerical framework that uses only simulations of returns for estimating risk budg
Externí odkaz:
http://arxiv.org/abs/2302.01196
Autor:
Pesenti, Lucas, Vladu, Adrian
We introduce a new algorithmic framework for discrepancy minimization based on regularization. We demonstrate how varying the regularizer allows us to re-interpret several breakthrough works in algorithmic discrepancy, ranging from Spencer's theorem
Externí odkaz:
http://arxiv.org/abs/2211.05509