In this paper I describe how miscommunication problems are dealt with in the spoken language system DIALOGOS. The dialogue module of the system exploits dialogic expectations in a twofold way: to model what future user utterance might be about (pre...
The <1 kb state machine hook for React (⭐ 2408)
Sep 2, 2014 · As for barrel length, no one barrel length is inherently more accurate as far as the gun, itself, should you put the gun in a machine rest. In other words, there can be as much raw …
The membership inference attack (MIA) is a popular paradigm for compromising the privacy of a machine learning (ML) model. MIA exploits the natural inclination of ML models to overfit upon the training data. MIAs are trained to distinguish between tr...
2008-02-28 at the Wayback Machine." Houston Independent School District. Shaw, Rissa (May 30, 2020). "George Floyd's former teammate wants him remembered as more
Techniques combining machine learning with translation to automated reasoning have recently become an important component of formal proof assistants. Such "hammer" tech- niques complement traditional proof assistant automation as implemented by tacti...
Sep 19, 2025 · Using generative AI to help robots jump higher and land safely MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that …
Diabetes is one of the chronic diseases that has been discovered for decades. However, several cases are diagnosed in their late stages. Every one in eleven of the world's adult population has diabetes. Forty-six percent of people with diabetes have...
Machine learning approach to detect whether patien has the diabetes or not. Data cleaning, visualization, modeling and cross validation applied (⭐ 112)
Predict Diabetes using Machine Learning. (⭐ 164)
? A functional, immutable Finite State Machine library (⭐ 2152)
robot or robots in Wiktionary, the free dictionary. A robot is a virtual or mechanical artificial agent, usually an electro-mechanical machine. Robot
There have been a number of recent proposals to enhance the performance of machine learning strategies for collider physics by combining many distinct events into a single ensemble feature. To evaluate the efficacy of these proposals, we study the co...
This thesis examines a modern concept for machine numbers based on interval arithmetic called 'Unums' and compares it to IEEE 754 floating-point arithmetic, evaluating possible uses of this format where floating-point numbers are inadequate. In the c...
Understanding and monitoring aquatic biodiversity is critical for ecological health and conservation efforts. This paper proposes SuoiAI, an end-to-end pipeline for building a dataset of aquatic invertebrates in Vietnam and employing machine learning...
Racial bias in medicine, such as in dermatology, presents significant ethical and clinical challenges. This is likely to happen because there is a significant underrepresentation of darker skin tones in training datasets for machine learning models....
This is a set of counterterrorism machine learning and data processing tools (⭐ 0)
Machine Learning for Counterterrorism. (⭐ 2)
Random Projection is a foundational research topic that connects a bunch of machine learning algorithms under a similar mathematical basis. It is used to reduce the dimensionality of the dataset by projecting the data points efficiently to a smaller...
This study evaluates the application of predictive analytics for real-time cyber-attack detection and response, focusing on how statistical and machine learning methods can improve decision-making in Security Operations Centers (SOCs). Using a curate...