Search Results - "Parameswaran, Aditya G"

Leveraging Analysis History for Improved In Situ Visualization Recommendation by EPPerson, Will, Jung‐Lin Lee, Doris, Wang, Leijie, Agarwal, Kunal, Parameswaran, Aditya G., Moritz, Dominik, Perer, Adam

“…Existing visualization recommendation systems commonly rely on a single snapshot of a dataset to suggest visualizations to users. However, exploratory data…”
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Efficient and Compact Spreadsheet Formula Graphs by Tang, Dixin, Chen, Fanchao, De Leon, Christopher, Wattanawaroon, Tana, Yun, Jeaseok, Seshadri, Srinivasan, Parameswaran, Aditya G.

“…Spreadsheets are one of the most popular data analysis tools, wherein users can express computation as formulae alongside data. The ensuing dependencies are…”
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DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing by Shankar, Shreya, Parameswaran, Aditya G, Wu, Eugene

“…Analyzing unstructured data, such as complex documents, has been a persistent challenge in data processing. Large Language Models (LLMs) have shown promise in…”
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"We Have No Idea How Models will Behave in Production until Production": How Engineers Operationalize Machine Learning by Shankar, Shreya, Garcia, Rolando, Hellerstein, Joseph M, Parameswaran, Aditya G

“…Proc. ACM Hum.-Comput. Interact. 8, CSCW1, Article 206 (April 2024) Organizations rely on machine learning engineers (MLEs) to deploy models and maintain ML…”
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Rethinking Streaming Machine Learning Evaluation by Shankar, Shreya, Herman, Bernease, Parameswaran, Aditya G

“…While most work on evaluating machine learning (ML) models focuses on computing accuracy on batches of data, tracking accuracy alone in a streaming setting…”
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Moving Fast With Broken Data by Shankar, Shreya, Fawaz, Labib, Gyllstrom, Karl, Parameswaran, Aditya G

“…Machine learning (ML) models in production pipelines are frequently retrained on the latest partitions of large, continually-growing datasets. Due to…”
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Transactional Panorama: A Conceptual Framework for User Perception in Analytical Visual Interfaces by Tang, Dixin, Fekete, Alan, Gupta, Indranil, Parameswaran, Aditya G

“…Many tools empower analysts and data scientists to consume analysis results in a visual interface, such as a dashboard. When the underlying data changes, these…”
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Operationalizing Machine Learning: An Interview Study by Shankar, Shreya, Garcia, Rolando, Hellerstein, Joseph M, Parameswaran, Aditya G

“…Organizations rely on machine learning engineers (MLEs) to operationalize ML, i.e., deploy and maintain ML pipelines in production. The process of…”
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Towards Accurate and Efficient Document Analytics with Large Language Models by Lin, Yiming, Hulsebos, Madelon, Ma, Ruiying, Shankar, Shreya, Zeigham, Sepanta, Parameswaran, Aditya G, Wu, Eugene

“…Unstructured data formats account for over 80% of the data currently stored, and extracting value from such formats remains a considerable challenge. In…”
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Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences by Shankar, Shreya, Zamfirescu-Pereira, J. D, Hartmann, Björn, Parameswaran, Aditya G, Arawjo, Ian

“…Due to the cumbersome nature of human evaluation and limitations of code-based evaluation, Large Language Models (LLMs) are increasingly being used to assist…”
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Flow with FlorDB: Incremental Context Maintenance for the Machine Learning Lifecycle by Garcia, Rolando, Kallanagoudar, Pragya, Anand, Chithra, Chasins, Sarah E, Hellerstein, Joseph M, Kerrison, Erin Michelle Turner, Parameswaran, Aditya G

“…In this paper we present techniques to incrementally harvest and query arbitrary metadata from machine learning pipelines, without disrupting agile practices…”
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Human-powered Data Management by Parameswaran, Aditya G

“…Fully automated algorithms are inadequate for a number of data analysis tasks, especially those involving images, video, or text. Thus, there is often a need…”
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Revisiting Prompt Engineering via Declarative Crowdsourcing by Parameswaran, Aditya G, Shankar, Shreya, Asawa, Parth, Jain, Naman, Wang, Yujie

“…Large language models (LLMs) are incredibly powerful at comprehending and generating data in the form of text, but are brittle and error-prone. There has been…”
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Efficient and Compact Spreadsheet Formula Graphs by Tang, Dixin, Chen, Fanchao, De Leon, Christopher, Wattanawaroon, Tana, Yun, Jeaseok, Seshadri, Srinivasan, Parameswaran, Aditya G

“…Spreadsheets are one of the most popular data analysis tools, wherein users can express computation as formulae alongside data. The ensuing dependencies are…”
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SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelines by Shankar, Shreya, Li, Haotian, Asawa, Parth, Hulsebos, Madelon, Lin, Yiming, Zamfirescu-Pereira, J. D, Chase, Harrison, Fu-Hinthorn, Will, Parameswaran, Aditya G, Wu, Eugene

“…Large language models (LLMs) are being increasingly deployed as part of pipelines that repeatedly process or generate data of some sort. However, a common…”
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Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time by Xin, Doris, Petersohn, Devin, Tang, Dixin, Wu, Yifan, Gonzalez, Joseph E, Hellerstein, Joseph M, Joseph, Anthony D, Parameswaran, Aditya G

“…We propose opportunistic evaluation, a framework for accelerating interactions with dataframes. Interactive latency is critical for iterative,…”
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Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows by Lee, Doris Jung-Lin, Tang, Dixin, Agarwal, Kunal, Boonmark, Thyne, Chen, Caitlyn, Kang, Jake, Mukhopadhyay, Ujjaini, Song, Jerry, Yong, Micah, Hearst, Marti A, Parameswaran, Aditya G

“…Exploratory data science largely happens in computational notebooks with dataframe APIs, such as pandas, that support flexible means to transform, clean, and…”
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DataHub: Collaborative Data Science & Dataset Version Management at Scale by Bhardwaj, Anant, Bhattacherjee, Souvik, Chavan, Amit, Deshpande, Amol, Elmore, Aaron J, Madden, Samuel, Parameswaran, Aditya G

“…Relational databases have limited support for data collaboration, where teams collaboratively curate and analyze large datasets. Inspired by software version…”
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