Author: Vineet Kumar

Vineet Kumar
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Vineet Kumar is a consulting intern at MarktechPost. He is currently pursuing his BS from the Indian Institute of Technology(IIT), Kanpur. He is a Machine Learning enthusiast. He is passionate about research and the latest advancements in Deep Learning, Computer Vision, and related fields.

Multi-Task Learning with Regression and Classification Tasks: MTLComb

In machine learning, multi-task learning (MTL) has emerged as a powerful paradigm that enables concurrent training of multiple interrelated algorithms. By exploiting the inherent...

Machine Learning Revolutionizes Path Loss Modeling with Simplified Features

Accurate propagation modeling is paramount for effective radio deployments, coverage analysis, and interference mitigation in wireless communications. Path loss modeling, a widely adopted approach,...

The Pursuit of the Platonic Representation: AI’s Quest for a Unified Model of Reality

As Artificial Intelligence (AI) systems advance, a fascinating trend has emerged: their representations of data across different architectures, training objectives, and even modalities seem...

The Art of Memory Mosaics: Unraveling AI’s Compositional Prowess

Have you ever wondered how current AI systems, like those powering chatbots and language models, can comprehend and generate natural language so effectively? The...

Breaking Down Barriers: Scaling Multimodal AI with CuMo

The advent of large language models (LLMs) like GPT-4 has sparked excitement around enhancing them with multimodal capabilities to understand visual data alongside text....

How ‘Chain of Thought’ Makes Transformers Smarter

Large Language Models (LLMs) like GPT-3 and ChatGPT exhibit exceptional capabilities in complex reasoning tasks such as mathematical problem-solving and code generation, far surpassing...

AnchorGT: A Novel Attention Architecture for Graph Transformers as a Flexible Building Block to Improve the Scalability of a Wide Range of Graph Transformer...

Transformers have taken the machine learning world by storm with their powerful self-attention mechanism, achieving state-of-the-art results in areas like natural language processing and...

Bayesian Optimization for Preference Elicitation with Large Language Models

Imagine you're trying to help a friend find their favorite movie to watch, but they're not quite sure what they're in the mood for....

NASGraph: A Novel Graph-based Machine Learning Method for NAS Featuring Lightweight (CPU-only) Computation and is Data-Agnostic and Training-Free

Designing state-of-the-art deep learning models is an incredibly complex challenge that researchers have been tackling using an approach called Neural Architecture Search (NAS). The...

A Novel AI Approach to Enhance Language Models: Multi-Token Prediction

Language models are incredibly powerful tools that can understand and generate human-like text by learning patterns from massive datasets. However, the traditional method of...

Researchers from Stanford and Amazon Developed STARK: A Large-Scale Semi-Structure Retrieval AI Benchmark on Textual and Relational Knowledge Bases

Imagine you're looking for the perfect gift for your kid – a fun yet safe tricycle that ticks all the boxes. You might search...

A New AI Approach for Estimating Causal Effects Using Neural Networks

Have you ever wondered how we can determine the true impact of a particular intervention or treatment on certain outcomes? This is a crucial...

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