Zobrazeno 1 - 10
of 7 844
pro vyhledávání: '"P Nagaraj"'
Inferring causal relationships in the decision-making processes of machine learning algorithms is a crucial step toward achieving explainable Artificial Intelligence (AI). In this research, we introduce a novel causality measure and a distance metric
Externí odkaz:
http://arxiv.org/abs/2411.01881
Autor:
S, Remya Ajai A, Nagaraj, Nithin
Inspired by the human brain's structure and function, Artificial Neural Networks (ANN) were developed for data classification. However, existing Neural Networks, including Deep Neural Networks, do not mimic the brain's rich structure. They lack key f
Externí odkaz:
http://arxiv.org/abs/2410.23351
We consider the problem of high-dimensional heavy-tailed statistical estimation in the streaming setting, which is much harder than the traditional batch setting due to memory constraints. We cast this problem as stochastic convex optimization with h
Externí odkaz:
http://arxiv.org/abs/2410.20135
Autor:
Hsieh, Jane, Zhang, Angie, Kim, Seyun, Rao, Varun Nagaraj, Dalal, Samantha, Mateescu, Alexandra, Grohmann, Rafael Do Nascimento, Eslami, Motahhare, Lee, Min Kyung, Zhu, Haiyi
Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulations. The CSCW and HCI communities increasingly turn to worker data col
Externí odkaz:
http://arxiv.org/abs/2409.00737
Autor:
Nagaraj, Sujay, Goodwin, Andrew J., Lopushanskyy, Dmytro, Eytan, Danny, Greer, Robert W., Goodfellow, Sebastian D., Assadi, Azadeh, Jayarajan, Anand, Goldenberg, Anna, Mazwi, Mjaye L.
Central Venous Lines (C-Lines) and Arterial Lines (A-Lines) are routinely used in the Critical Care Unit (CCU) for blood sampling, medication administration, and high-frequency blood pressure measurement. Judiciously accessing these lines is importan
Externí odkaz:
http://arxiv.org/abs/2409.00041
Applying Reinforcement Learning (RL) to Restless Multi-Arm Bandits (RMABs) offers a promising avenue for addressing allocation problems with resource constraints and temporal dynamics. However, classic RMAB models largely overlook the challenges of (
Externí odkaz:
http://arxiv.org/abs/2408.05686
We prove that the direct image of an anti-ample vector bundle is anti-ample under any finite flat morphism of non-singular projective varieties. In the second part we prove some properties of big and nef vector bundles. In particular it is shown that
Externí odkaz:
http://arxiv.org/abs/2407.01151
Autor:
Rao, Varun Nagaraj, Choudhary, Siddharth, Deshpande, Aditya, Satzoda, Ravi Kumar, Appalaraju, Srikar
The scaling of large language models to encode all the world's knowledge in model parameters is unsustainable and has exacerbated resource barriers. Retrieval-Augmented Generation (RAG) presents a potential solution, yet its application to vision-lan
Externí odkaz:
http://arxiv.org/abs/2406.19150
Autor:
Hickok, Truman, Nagaraj, Sriram
Blind signal separation (BSS) is an important and challenging signal processing task. Given an observed signal which is a superposition of a collection of unknown (hidden/latent) signals, BSS aims at recovering the separate, underlying signals from o
Externí odkaz:
http://arxiv.org/abs/2406.15623
Autor:
Nagaraj, Sriram, Hickok, Truman
This paper is aimed at using the newly developing field of physics informed machine learning (PIML) to develop models for predicting the remaining useful lifetime (RUL) aircraft engines. We consider the well-known benchmark NASA Commercial Modular Ae
Externí odkaz:
http://arxiv.org/abs/2406.15619