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pro vyhledávání: '"Gupta Varun"'
We present an efficient reduction that converts any machine learning algorithm into an interactive protocol, enabling collaboration with another party (e.g., a human) to achieve consensus on predictions and improve accuracy. This approach imposes cal
Externí odkaz:
http://arxiv.org/abs/2411.19791
Autor:
Kumar Praveen, Gupta Varun
Publikováno v:
ITM Web of Conferences, Vol 54, p 01013 (2023)
Preservation of the artworks has historical and cultural importance. However, with time, environmental factors severely affect artworks, and these damages are often complicated to repair manually and through traditional methods. We propose a method t
Externí odkaz:
https://doaj.org/article/9fd9bf8e70724ee7ac7b3b4caea85625
Autor:
Saravanan, Darshana, Singh, Darshan, Gupta, Varun, Khan, Zeeshan, Gandhi, Vineet, Tapaswi, Makarand
Compositionality is a fundamental aspect of vision-language understanding and is especially required for videos since they contain multiple entities (e.g. persons, actions, and scenes) interacting dynamically over time. Existing benchmarks focus prim
Externí odkaz:
http://arxiv.org/abs/2406.10889
There is a long history in machine learning of model ensembling, beginning with boosting and bagging and continuing to the present day. Much of this history has focused on combining models for classification and regression, but recently there is inte
Externí odkaz:
http://arxiv.org/abs/2405.16752
We study a repeated contracting setting in which a Principal adaptively chooses amongst $k$ Agents at each of $T$ rounds. The Agents are non-myopic, and so a mechanism for the Principal induces a $T$-round extensive form game amongst the Agents. We g
Externí odkaz:
http://arxiv.org/abs/2402.17108