Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
About Me
Archive Layout with Content
Posts by Category
Posts by Collection
CV
Markdown
Page not in menu
Page Archive
Portfolio
Sitemap
Posts by Tags
Talk map
Talks and presentations
Teaching
Terms and Privacy Policy
Blog posts
Jupyter notebook markdown generator
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
publications
Conformal Prediction for Event Stream Data
We propose a conformal prediction framework tailored to temporal point processes, resolving challenges posed by their continuous-time nature, temporal dependence, and violation of exchangeability assumptions. We establish rigorous coverage guarantees under mild assumptions of periodic stationarity and \(\beta\)-mixing, and extend the theoretical results to Hawkes processes and non-periodic stationary processes.
Residual TPP: A Unified Lightweight Approach for Event Stream Data Analysis
Published in Forty-second International Conference on Machine Learning (ICML), 2025
We introduce Residual TPP, a novel, unified, and lightweight approach that leverages the strengths of both classical temporal point processes (TPPs) and expressive neural TPPs to achieve superior performance. Specifically, we propose the Residual Events Decomposition (RED) technique for TPPs, which defines a weight function to quantify how well the intensity function captures the event characteristics. The RED serves as a flexible, plug-and-play module that can be integrated with any TPP model in a wide range of tasks.
Auto-scaling Continuous Memory for GUI Agents
We introduce a continuous memory framework for GUI agents, along with an auto-scaling data flywheel that autonomously discovers environments, generates tasks, collects trajectories, and performs quality evaluation. Our method achieves state-of-the-art results across multiple real-world GUI benchmarks.
An Implementation-Friendly Model-Agnostic Approach for Process Data Analysis
Published in Journal of the American Statistical Association, 2026
We develop a comprehensive framework for analyzing computer-based problem-solving assessments that predicts students progression toward correct answers in real-time and summarizes it into probability trajectories. The resulting curves are robust, model-agnostic statistics that enable multiple downstream applications.
Sparse Regression with $\ell_0$ Constraints for $\alpha$-Mixing Time Series: Algorithms and Guarantees
Published in Forty-third International Conference on Machine Learning (ICML), 2026
We study exact sparse time-series modeling via $\ell_0$-constrained least squares under temporal dependence. For stationary $\alpha$-mixing Gaussian processes with sparse coefficients, we establish high-probability RSC/RSS for the empirical quadratic loss and obtain nonasymptotic statistical guarantees for exact sparse algorithms such as iterative hard thresholding (IHT).