A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.

BrainIAC analyzes brain scans across diseases, learns from minimal data, offers hope for rare condition diagnosis.

Analysis Of Section 3(k) Of The Patents Act, 1970. Legal News and Analysis - India - Intellectual Property - Conventus Law ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

This note examines the utility of pseudorandom variables (prv) in Global Search and Optimization (GSO) using Central Force Optimization (CFO) as an example. Most GSO metaheuristics are stochastic in ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

Abstract: The random Kaczmarz (RK) algorithm is an iterative method to solve overdetermined linear systems and serves as a representative example of row action methods. In this paper, we propose a ...

In this video, we explore why Spotify's shuffle feature isn't truly random and operates based on an algorithm. We discuss the reasons behind our preferences for non-random shuffle, the results of an ...

Researchers have successfully used a quantum algorithm to solve a complex century-old mathematical problem long considered impossible for even the most powerful conventional supercomputers. The ...

Abstract: A probabilistic approach is considered for robust optimization, where a convex objective function is minimized subject to a parameter dependent convex constraint. A novel sequential ...

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