A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New method estimates animal density using acoustic data, accounting for unknown call identities.
MOSS optimizes decision rules for accuracy and stability.
One non-invasive way to study frog communities is by analyzing long-term samples of acoustic material containing calls. This immense task has been optimized by the development of Machine Learning tools to extract ecological information. We explored a likelihood-ratio audio detector based on Gaussian mixture model class…
In general, object identification tends not to work well on ambiguous, amorphous objects such as vegetation. In this study, we developed a simple but effective approach to identify ambiguous objects and applied the method to several moss species. As a result, the model correctly classified test images with accuracy mor…
New algorithm reduces worst-case regret for heavy-tailed bandits.
New findings show many popular bandit algorithms are unstable, contradicting minimax optimality.
The paper analyzes the sliding regret of stochastic bandit algorithms.
Deep learning identifies frog species and detects new ones.
Diagonal Frog: High-order positivity-preserving FD schemes for anisotropic Fokker-Planck equations
Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality, by either selecting a subset of features or removing unrelated ones. This paper presents …
Data poisoning is an attack on machine learning models wherein the attacker adds examples to the training set to manipulate the behavior of the model at test time. This paper explores poisoning attacks on neural nets. The proposed attacks use "clean-labels"; they don't require the attacker to have any control over the …
In this article, a compact finite difference method is proposed for pricing European and American options under jump-diffusion models. Partial integro-differential equation and linear complementary problem governing European and American options respectively are discretized using Crank-Nicolson Leap-Frog scheme. In pro…
Efficient active learning method defends against malicious mislabeling and data poisoning attacks.
This anniversary paper is an occasion to recall some of the events that shaped institutional econophysics. But in these thoughts about the evolution of econophysics in the last 15 years we also express some concerns. Our main worry concerns the relinquishment of the simplicity requirement. Ever since the groundbreaking…
We consider -armed stochastic bandits and consider cumulative regret bounds up to time . We are interested in strategies achieving simultaneously a distribution-free regret bound of optimal order and a distribution-dependent regret that is asymptotically optimal, that is, matching the lower b…
New backdoor attacks in FL can fool models on rare inputs.
In recent years, a variety of effective neural network-based methods for anomaly and cyber attack detection in industrial control systems (ICSs) have been demonstrated in the literature. Given their successful implementation and widespread use, there is a need to study adversarial attacks on such detection methods to b…