Professor Yinyu Ye in town (again)!

Always a delight to learn from Professor Ye :) (He was in Shanghai 2023 Winter and I have my LP book signed by him!!!) Prof. Yinyu Ye teaching at SIMIS. Day one of lectures on optimization and a bit market design. Professor Yinyu Ye is currently visiting the Shanghai Institute for Mathematical and Interdisciplinary Sciences (SIMIS), delivering a lecture series on Optimization Methods for Data Science, Machine Learning, and AI....

May 7, 2025

A Little Mozart Wisdom

My advisor once told me what makes Così fan tutte so special and his favourite, is Mozart’s quiet masterpiece of tolerance. Mozart doesn’t judge anyone for being ridiculous or impulsive or foolish or fickle. He just observes—with a kind of tolerant wit—and turns the whole thing into music that smiles at human nature instead of scolding it. OK, so he’ll probably forgive me for being at the Cosi fan tutte’s LA opera premier but drank just enogh wine just to sleep through the 2nd act…...

May 6, 2025

WWW Paper | Mitigating the Participation Bias by Balancing Extreme Ratings

“Only people who are extremely satisfied or extremely pissed off would rate the products—how to aggregate the real ratings?"—— Mitigating the Participation Bias by Balancing Extreme Ratings Yongkang Guo, Yuqing Kong, Jialiang Liu Rating aggregation plays a crucial role in various fields, such as product recommendations, hotel rankings, and teaching evaluations. However, traditional averaging methods can be affected by participation bias, where some raters do not participate in the rating process, leading to potential distortions....

May 5, 2025

Consumerism Gossip VI | Coffee, Rankings, and Quiet Ads

My ballet class got rained out, so I ducked into a cozy café—and somehow ended up learning a bit more about Meituan and Ele.me’s business models over two cappuccinos—real coffee talk. In that café, when the barista handed the delivery guy one packed coffee. Intro: On these food delivery platforms, cafés are ranked for visibility. The higher the rank, the more orders roll in. And while it’s no surprise that paying to jump the line (read: sponsored listings) exists, what is surprising is how quietly the game is being played—not all money-boosted rankings are labeled....

May 5, 2025

WWW25 Paper | Supernotes for Twitter's Community Notes

Awesome paper I came across in WWW25’, using LLM to summarize a super note on top of all the community notes: Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking (Courtesy to Soham’s website for the info) Soham De, Michiel A. Bakker, Jay Baxter, and Martin Saveski The ACM Web Conference. 2025 X’s Community Notes, a crowd-sourced fact-checking system, allows users to annotate potentially misleading posts. Notes rated as helpful by a diverse set of users are prominently displayed below the original post....

May 3, 2025

Manon at the Sydney Opera House

I watched the Australian Ballet’s 2025 season Manon at the Sydney Opera House. Mia Heathcote danced Manon tonight—she’s a soloist now, but her technique is amazing and I believe she will rise up to be principal soon. Manon’s story is unconventional for ballet where the heroine is usually, well, not a ‘slut’. The synopsis is centered around Manon, the young, beautiful but poor woman with nothing but pretty privilege, torn to choose between her love for the impoverished student Des Grieux and the allure of wealth of Monsieur G....

May 2, 2025

WWW25 Paper | Preference + Relevance = Behavior Modeling Space Reconstruction

My advisor was busy during tea break so I was sent for the paper’s oral presentation. His loss ;) Behavior Modeling Space Reconstruction for E-Commerce Search Wang et al. WWW2025. https://doi.org/10.48550/arXiv.2501.18216 Delivering superior search services is crucial for enhancing customer experience and driving revenue growth. Conventionally, search systems model user behaviors by combining user preference and query item relevance statically, often through a fixed logical ‘and’ relationship. This paper reexamines existing approaches through a unified lens using both causal graphs and Venn diagrams, uncovering two prevalent yet significant issues: entangled preference and relevance effects, and a collapsed modeling space....

May 1, 2025

WWW25 Paper Reading Note (best paper) | Inverse Reinforcement Learning for Classifying Reddit Users

ABSOLUTELY AMAZING work: Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study Yuan, Schneider and Rizoiu, WWW2025. Openreview. DOI: https://doi.org/10.1145/3696410.3714618. Arxiv. Online communities play a critical role in shaping societal discourse and influencing collective behavior in the real world. The tendency for people to connect with others who share similar characteristics and views, known as homophily, plays a key role in the formation of echo chambers which further amplify polarization and division....

April 30, 2025

WWW25 Paper Reading Note | Transparency? In This Economy?

This is a reading note of an accepted oral paper at WWW2025: Welcome to the Dark Side — Analyzing the Revenue Flows of Fraud in the Online Ad Ecosystem By Emmanouil Papadogiannakis, Nicolas Kourtellis, Panagiotis Papadopoulos and Evangelos Markatos. Link: https://doi.org/10.1145/3696410.3714899 The online ad ecosystem is a mess—a densely tangled web of players with overlapping roles, and worse, a dictionary full of confusing terminologies. This paper takes a flashlight to one particularly shadowy corner (ad fraud?...

April 29, 2025

WWW25 Keynote | The AI Revolution in Time Series - Challenges and Opportunities, by Yan Liu from USC

(Btw, all the WWW keynotes can be found here.) Foundation models are large, pre-trained neural network trained on broad, diverse time series data with the goal of supporting many downstream tasks (forecasting, anomaly detection, causal inference, generation) across different domains. It’s like GPT-4, but for time series analysis. 🔹 Core Capabilities of a Time Series Foundation Model: Prediction — short-term, long-term, multivariate Analysis — pattern discovery, representation learning Causal Inference — learning and modeling causal relationships over time Generation — synthetic time series for simulation or augmentation Cross-domain transfer — one model works across finance, medicine, climate, etc....

April 28, 2025