10 citations · 12 across the 5 of their papers we have counts for
9 papers
Rethinking Data-driven Networking with Foundation Models: Challenges and Opportunities
Franck Le, Mudhakar Srivatsa, Raghu Ganti +1
Foundational models have caused a paradigm shift in the way artificial intelligence (AI) systems are built. They have had a major impact in natural language processing (NLP), and s…
State Action Separable Reinforcement Learning
Ziyao Zhang, Liang Ma, Kin K. Leung +2
Reinforcement Learning (RL) based methods have seen their paramount successes in solving serial decision-making and control problems in recent years. For conventional RL formulatio…
Neural Network Tomography
Liang Ma, Ziyao Zhang, Mudhakar Srivatsa
Network tomography, a classic research problem in the realm of network monitoring, refers to the methodology of inferring unmeasured network attributes using selected end-to-end pa…
SENSE: Semantically Enhanced Node Sequence Embedding
Swati Rallapalli, Liang Ma, Mudhakar Srivatsa +4
Effectively capturing graph node sequences in the form of vector embeddings is critical to many applications. We achieve this by (i) first learning vector embeddings of single grap…
neuralRank: Searching and ranking ANN-based model repositories
Nirmit Desai, Linsong Chu, Raghu K. Ganti +2
Widespread applications of deep learning have led to a plethora of pre-trained neural network models for common tasks. Such models are often adapted from other models via transfer…
Actor Conditioned Attention Maps for Video Action Detection
Oytun Ulutan, Swati Rallapalli, Mudhakar Srivatsa +2
While observing complex events with multiple actors, humans do not assess each actor separately, but infer from the context. The surrounding context provides essential information…