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Found 6 papers, 2 papers with code
Autonomous Sparse Mean-CVaR Portfolio Optimization
The $\ell_0$-constrained mean-CVaR model poses a significant challenge due to its NP-hard nature, typically tackled through combinatorial methods characterized by high computational demands.
A De-singularity Subgradient Approach for the Extended Weber Location Problem
The extended Weber location problem is a classical optimization problem that has inspired some new works in several machine learning scenarios recently.
Invariant Risk Minimization Is A Total Variation Model
Invariant risk minimization (IRM) is an arising approach to generalize invariant features to different environments in machine learning.
Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach
Invariant representation learning (IRL) encourages the prediction from invariant causal features to labels de-confounded from the environments, advancing the technical roadmap of out-of-distribution (OOD) generalization.
An Investigation of Darwiche and Pearl's Postulates for Iterated Belief Update
Firstly, we present a modification of the original KM postulates based on belief states.
Reweighted Price Relative Tracking System for Automatic Portfolio Optimization
In the portfolio optimizing stage, a novel tracking system with a generalized increasing factor is proposed to maximize the future wealth of next period.
