Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...
Abstract: The robust parameter and output estimation for linear parameter varying (LPV) time-delay system with output data contaminated with outliers and subjected to randomly missing measurements are ...
Abstract: This article addresses the adaptive radar target detection problem in the presence of Gaussian interference with unknown statistical properties. To this end, the problem is first formulated ...
This digital series—featuring scholars from CSIS Futures Lab and AI evaluation experts from Scale AI—explores how large language models approach critical foreign policy decision-making scenarios. This ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Create a hybrid pricing model using the ICE model and traditional valuation Conclusion: A 'hybrid pricing model' that integrates the ICE model (expected value/attractiveness) and traditional valuation ...
For contributor/development setup (from source), see CONTRIBUTING.md. Let's start with a tiny DSL-based example that builds a simple circuit, evaluates log-likelihood ...
This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2018. Contributed by Andrea L. Bertozzi, April 15, 2020 (sent for review ...
A faster variant running a single density greedy yields a $1/2$ approximation (Algorithm 7). For the non-monotone case, the algorithm adopts the "density greedy + random deletion with fixed ...
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