Once upon a time, courts asked only three questions: Is there urgency? Is there merit? Is there jurisdiction? Today, in the trial courts of Tamil Nadu, it depends on scanner resolution, OCR accuracy ...

Shortest path algorithms sit at the heart of modern graph theory and many of the systems that move people, data, and goods around the world. After nearly seventy years of relying on the same classic ...

The original version of this story appeared in Quanta Magazine. Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price.

From powering search engines to securing data and optimizing networks, algorithms underpin nearly every aspect of modern technology. Understanding how efficiently they can solve problems — and where ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

import torch @torch.compile(backend="inductor") def fn(src, index, base_tensor): src = src + 10 torch.use_deterministic_algorithms(True) base_tensor.scatter_(0, index ...

Abstract: This paper proposes a novel algorithm for sentence formation in Tamil Language from the Enconverted UNL Knowledge graph. Universal Networking language is an intermediary representation of ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

Ever wondered how social media platforms decide how to fill our feeds? They use algorithms, of course, but how do these algorithms work? A series of corporate leaks over the past few years provides a ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

Abstract: Automatic Text Summarization represents one of the most imperative and challenging applications of Natural Language Processing (NLP). Text Summarization extracts key information from a long ...