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  • The annual ACM SIGKDD Conference on Knowledge Discovery and Data Mining is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share ideas, research results and experiences.
    August 3 - 7, 2025
    Toronto, Ontario
  • The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses.
    June 11 - 15, 2025
    Nashville, Tennessee
  • The flagship conference of the IEEE Robotics and Automation Society (RAS), ICRA brings together the world’s top researchers and industry leaders to share ideas, exchange knowledge, and advance the field of robotics for the benefit of humanity.
    May 19 - 23, 2025
    Atlanta, GA
  • The North American Chapter of the Association for Computational Linguistics (NAACL) provides a regional focus for ACL members in North, Central, and South America, organizes annual conferences, promotes cooperation and information exchange among related scientific and professional societies, encourages and facilitates ACL membership by people and institutions in the Americas, and provides a source of information on regionalRead more
    April 29 - May 4, 2025
    Albuquerque, New Mexico
  • Since the invention of the World Wide Web in 1989, The Web Conference is a yearly international academic conference on the topic of the future direction of the World Wide Web. This conference has been the premier venue to present and discuss progress in research, development, standards, and applications of the topics related to the Web.
    April 28 - May 2, 2025
    Sydney, Australia
  • The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning.
    April 24 - 28, 2025
    Singapore
  • Data Scientist
  • Applied Scientist
  • Sina Shaham, Arash Hajisafi, Minh K. Quan, Dinh C. Nguyen, Bhaskar Krishnamachari, Charith Peris, Gabriel Ghinita, Cyrus Shahabi, Pubudu N. Pathirana
    IEEE Transactions on Artificial Intelligence
    2025
    Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the literature with the aim of reducing utility loss in achieving them. Despite the significant interest attracted from both academia and industry, there remains an immediate demand for more in-depth research to unravel how these
  • CLeaR 2025
    2025
    Which set of features was responsible for a certain output of a machine learning model? Which components caused the failure of a cloud computing application? These are just two examples of questions we are addressing in this work by Identifying Coalition-based Explanations for Common and Rare Events in Any Model (ICECREAM). Specifically, we propose an information-theoretic quantitative measure for the influence
  • Frontiers in Artificial Intelligence
    2025
    As we become increasingly dependent on technology in our daily lives, the usability of HCIs is a key driver of individual empowerment for us all. A primary focus of AI systems has been to make HCIs easier to use by identifying what users need and agentively taking over some of the cognitive work users would have otherwise performed, as such, they are becoming our delegates. To become effective and reliable
  • Which set of features was responsible for a certain output of a machine learning model? Which components caused the failure of a cloud computing application? These are just two examples of questions we are addressing in this work by Identifying Coalition-based Explanations for Common and Rare Events in Any Model (ICECREAM). Specifically, we propose an information-theoretic quantitative measure for the influence
  • Autonomy via agents based on large language models (LLMs) that can carry out personalized yet standardized tasks presents a significant opportunity to drive human efficiency. There is an emerging need and interest in automating web tasks (e.g., booking a hotel for a given date within a budget). Being a practical use case itself, the web agent also serves as an important proof-of-concept example for various
  • AgentOccam offers a simple but strong baseline for LLM-based web agents. By providing a URL and the task you want it to perform, AgentOccam can execute it for you. Its simplicity and effectiveness allow you to run it directly, or adapt it into a larger pipeline for its executing web tasks, such as web information retrieval before processing the documents. Without using in-context examples, new agent roles
  • Economist
  • Data Scientist
  • Senior Manager, Research Science
  • Applied Scientist
  • Applied Scientist
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainableRead more