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8 results for V-shape

A well-constructed classification model highly depends on input feature subsets from a dataset, which may contain redundant, irrelevant, or noisy features. This challenge can be worse while dealing with medical datasets. The main aim of feature selection as a pre-processing task is to eliminate these features and selec…

2019-11-15abs ↗pdf ↗

Study models stock price recovery during COVID-19, distinguishing V and L-shape recoveries.

problem Analyzing stock price recovery during the COVID-19 pandemic.
method Developed a stock price model based on net-fund-flow and financial antifragility.
result Quality stocks with higher financial antifragility show V-shape recovery, while those with lower antifragility show L-shape recovery.

Investor aims to meet financial goals with deadlines and target amounts, considering stock trading costs.

problem Goal-based portfolio selection with fixed transaction costs.
method Stochastic Perron's method to show value function is unique viscosity solution to quasi-variational inequalities. Existence of optimal strategy established.
result Optimal trading strategy differs significantly from frictionless case, revealing complex regions and strategies.

Looped transformers outperform standard transformers in complex reasoning tasks due to a specific loss landscape geometry.

problem Understanding why looped transformers outperform standard transformers in complex reasoning tasks.
method Explained through loss landscape geometry, distinguishing between U-shaped and V-shaped valleys, and proposing SHIFT training strategy.
result Looped transformers' recursive architecture induces a River-V-Valley landscape, leading to better loss convergence and complex pattern learning.