Ali Vardasbi

As of December 2023, I have started my new position as a research scientist at Spotify.

Notes

Here I keep some highlights from the papers I read.

PhD

I joined the University of Amsterdam, IRLab as a Ph.D. on May 2019, under the supervision of Prof. Maarten de Rijke and Dr. Mostafa Dehghani. Our work on fair and unbiased learning to rank (LTR) from user interactions has led to several papers in SIGIR and CIKM. We also explored overparameterization and memorization/generalization in general machine learning.

In the summer of 2022, I interned in the machine translation team at Apple and extended my experience in sequence modeling, particularly transformers and state space models.

In the last year of my PhD (i.e., 2023), I have worked on generative Large Language Models (LLMs) and retrieval augmentation techniques in music recommendation as an intern at Spotify.

Thesis

Re-Examining Assumptions in Fair and Unbiased Learning to Rank. Amsterdam, December 2023.

Publications

Conferences

• Ali Vardasbi, Maarten de Rijke, Fernando Diaz, and Mostafa Dehghani. Group Membership bias. arxiv 2023.
• Fatemeh Sarvi, Ali Vardasbi, Mohammad Aliannejadi, Sebastian Schelter, and Maarten de Rijke. On the Impact of Outlier Bias on User Clicks. SIGIR 2023.
• Ming Li, Ali Vardasbi, Andrew Yates, and Maarten de Rijke. Repetition and Exploration in Sequential Recommendation: A Reproducibility Study. SIGIR 2023.
• Ali Vardasbi, Telmo Pessoa Pires, Robin M.~Schmidt, and Stephan Peitz. State Spaces Aren’t Enough: Machine Translation Needs Attention. EAMT 2023.
• Ali Vardasbi, Mostafa Dehghani, and Maarten de Rijke, Intersection of Parallels as an Early Stopping Criterion. In CIKM 2022. Codes
• Ali Vardasbi, Fatemeh Sarvi, and Maarten de Rijke, Probabilistic Permutation Graph Search: Black-Box Optimization for Fairness in Ranking In SIGIR 2022. Codes
• Ali Vardasbi, Maarten de Rijke, and Ilya Markov. Mixture-Based Correction for Position and Trust Bias in Counterfactual Learning to Rank. In CIKM 2021. Codes
• Hamed Bonab, Mohammad Aliannejadi, Ali Vardasbi, Evangelos Kanoulas, James Allan. Cross-Market Product Recommendation. In CIKM 2021.
• Ali Vardasbi, Harrie Oosterhuis, and Maarten de Rijke. When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank. In CIKM 2020. Codes
• Ali Vardasbi, Maarten de Rijke, and Ilya Markov. Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank. In SIGIR 2020. Codes
• Ali Vardasbi, Heshaam Faili, Masoud Asadpour. Eigenvalue Based Features for Semantic Sentence Similarity. In Artificial Intelligence and Signal Processing Conference (AISP). IEEE, October 2017.

Journals

• Ali Vardasbi, Heshaam Faili, Masoud Asadpour. Solving Submodular Text Processing Problems Using Influence Graphs. Social Network Analysis and Mining, 2019.
• Ali Vardasbi, Heshaam Faili, Masoud Asadpour. SWIM: Stepped Weighted Shell Decomposition Influence Maximization for Large-Scale Networks ACM Transactions on Information Systems (TOIS), 2017.