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arxiv.org/abs/2107.11986v2

Benign Adversarial Attack: Tricking Models for Goodness

In spite of the successful application in many fields, machine learning models today suffer from notorious problems like vulnerability to adversarial examples. Beyond falling into the cat-and-mouse game between adversarial attack and defense, this pa...

arxiv.org/abs/2503.11930v1

Generating a Biometrically Unique and Realistic Iris Database

The use of the iris as a biometric identifier has increased dramatically over the last 30 years, prompting privacy and security concerns about the use of iris images in research. It can be difficult to acquire iris image databases due to ethical conc...

arxiv.org/abs/2412.11996v1

On Differential Stability of a Class of Convex Optimization Problems

The recent results of An, Luan, and Yen [Differential stability in convex optimization via generalized polyhedrality. Vietnam J. Math. https://-doi.org/10.1007/s10013-024-00721-y] on differential stability of parametric optimization problems describe...

arxiv.org/abs/2507.11992v3

Understanding visual attention beehind bee-inspired UAV navigation

Bio-inspired design is often used in autonomous UAV navigation due to the capacity of biological systems for flight and obstacle avoidance despite limited sensory and computational capabilities. In particular, honeybees mainly use the sensory input o...

github.com/ushahidi/SMSSync

ushahidi/SMSSync

SMS gateway for Android powered phones (⭐ 1196)

github.com/xcesco/kripton

xcesco/kripton

A Java/Kotlin library for Android platform, to manage bean's persistence in SQLite, SharedPreferences, JSON, XML, Properties, Yaml, CBOR. (⭐ 119)

arxiv.org/abs/1907.11915v2

Electronic markets with multiple submodular buyers

We discuss the problem of setting prices in an electronic market that has more than one buyer. We assume that there are self-interested sellers each selling a distinct item that has an associated cost. Each buyer has a submodular valuation for purcha...

arxiv.org/abs/1909.11939v6

MERL: Multi-Head Reinforcement Learning

A common challenge in reinforcement learning is how to convert the agent's interactions with an environment into fast and robust learning. For instance, earlier work makes use of domain knowledge to improve existing reinforcement learning algorithms...