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Prasad Tadepalli

25 papers hereh-index 406.2k citations253 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author8
  • last author17

Across the 25 of 25 papers where every author was matched, so the position is known.

fields
  • cs.CL11
  • cs.AI7
  • cs.LG4
  • cs.CV2
  • cs.IR1
same name
  • Prasad Tadepalli — 7 papers, h 3
  • Prasad Tadepalli — 4 papers, h 3
  • Prasad Tadepalli — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedSaliency Learning: Teaching the Model Where to Pay Attention

12 citations · 34 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 1 cited

Adversarial Attacks on Combinatorial Multi-Armed Bandits

Rishab Balasubramanian, Jiawei Li, Prasad Tadepalli +3

We study reward poisoning attacks on Combinatorial Multi-armed Bandits (CMAB). We first provide a sufficient and necessary condition for the attackability of CMAB, a notion to capt…

cs.LG2022

Explainable Models via Compression of Tree Ensembles

Siwen Yan, Sriraam Natarajan, Saket Joshi +2

Ensemble models (bagging and gradient-boosting) of relational decision trees have proved to be one of the most effective learning methods in the area of probabilistic logic models…

cs.LG2020

DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs

Aayam Shrestha, Stefan Lee, Prasad Tadepalli +1

We study an approach to offline reinforcement learning (RL) based on optimally solving finitely-represented MDPs derived from a static dataset of experience. This approach can be a…

cs.LG2018★ 8 cited

Interactive Naming for Explaining Deep Neural Networks: A Formative Study

Mandana Hamidi-Haines, Zhongang Qi, Alan Fern +2

We consider the problem of explaining the decisions of deep neural networks for image recognition in terms of human-recognizable visual concepts. In particular, given a test set of…

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