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  1. Amit Ravindernath Sharma (born 13 April 1978) is an Indian film director and producer known for directing films like Badhaai ho (2018) and Maidaan (2024). In feature films, he is best known for the 2018 film Badhaai Ho, which was one of the highest grossing Bollywood films of 2018, having earned ₹220.34 crore ($31 million) as of December 2018.

  2. Amit Ravindernath Sharma is an Indian film director and ad filmmaker. He wanted to become an actor since his school days and used to participate in almost every plays of his school. He was introduced to the director Pradeep Sarkar through one of his mother’s friend.

    • Directing ‘Badhaai Ho' (2018)
    • Film Director and Ad Filmmaker
    • Amit Ravindernath Sharma
    • Amit Sharma1
    • Amit Sharma2
    • Amit Sharma3
    • Amit Sharma4
  3. Preserving causal constraints in counterfactual explanations for machine learning classifiers. D Mahajan, C Tan, A Sharma. arXiv preprint arXiv:1912.03277. , 2019. 233. 2019. Topology-aware task mapping for reducing communication contention on large parallel machines. T Agarwal, A Sharma, A Laxmikant, LV Kalé.

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  5. en.wikipedia.org › wiki › Amit_SharmaAmit Sharma - Wikipedia

    Amit Sharma may refer to: Amit Sharma (cricketer) Amit Sharma (director) Amit Sharma (youtuber) Amit Prakash Sharma, Indian parasitologist

  6. Amit Sharma is a computer scientist who works on predictive systems and causal inference at Microsoft. He has a PhD from Cornell University and has published papers on recommendation, social media, and natural language processing.

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  7. Sep 14, 2023 · Publications. Talks. Blog. Causal Inference. Contact. Amit Sharma. Principal Researcher. Microsoft Research India. 2022.07.25: Talk on necessity of causal inference for out-of-distribution generalization in prediction and decision-making at the Technion, Israel.

  8. Amit Sharma is a causal inference and machine learning researcher who works on designing and evaluating algorithmic interventions for societal impact. He has published papers on topics such as recommender systems, mental health helpline technology, and causal explanation for machine learning.

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