The conditional value at risk (CVaR) is a popular risk measure which enables risk-averse decision making under uncertainty. We consider maximizing the CVaR of a continuous submodular function, an extension of submodular set functions to a continuous domain. One example application is allocating a continuous amount of energy to each sensor in a network, with the goal of detecting intrusion or co...

Conditional value at risk (CVaR) has been widely used as a risk measure in finance. When the confidence level of CVaR is set close to 1, the CVaR risk measure approximates the extreme (worst scenario) risk measure. In this paper, we present a quantitative analysis of the relationship between the two risk measures and its impact on optimal decision making when we wish to minimize the respective ...

In this paper we address the problem of decision making within a Markov de-cision process (MDP) framework where risk and modeling errors are taken intoaccount. Our approach is to minimize a risk-sensitive conditional-value-at-risk(CVaR) objective, as opposed to a standard risk-neutral expectation. We refer tosuch problem as CVaR MDP. Our first contribution is to show that a CVaR...

We study a risk-constrained version of the stochastic shortest path (SSP) problem, where the risk measure considered is Conditional Value-at-Risk (CVaR). We propose two algorithms that obtain a locally risk-optimal policy by employing four tools: stochastic approximation, mini batches, policy gradients and importance sampling. Both the algorithms incorporate a CVaR estimation procedure, along t...

در مطالعات زمین‌شناسی و کانی‌شناسی، وجود پوشش‌ گیاهی سالم خشک پیکسل‌های حاوی اطلاعات طیفی اجتناب‌ناپذیر است. بنابراین، بازیابی حد زیرپیکسل، مانند برآورد میزان حضور یک کانی پیکسل از تصاویر سنجش دور ابرطیفی، مسئله‌ای مهم محسوب می‌شود. این پژوهش، روش عمق پیوستار اصلاح‌شدة اثر پوشش (VCCD)، برای کاهش تخمین کانی‌های هدف، با استفاده داده‌های طیف‌سنجی، آزمایشگاهی کانی‌شناسی هایپریون (Hyperion) اصلاح من...