3 citations · 3 across the 15 of their papers we have counts for
5 papers · 1 filter
Understanding the Role of Training Data in Test-Time Scaling
Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni
Test-time scaling improves the reasoning capabilities of large language models (LLMs) by allocating extra compute to generate longer Chains-of-Thoughts (CoTs). This enables models…
Differentially Private Model-X Knockoffs via Johnson-Lindenstrauss Transform
Yuxuan Tao, Adel Javanmard
We introduce a novel privatization framework for high-dimensional controlled variable selection. Our framework enables rigorous False Discovery Rate (FDR) control under differentia…
Differentially Private Synthetic Data Release for Topics API Outputs
Travis Dick, Alessandro Epasto, Adel Javanmard +5
The analysis of the privacy properties of Privacy-Preserving Ads APIs is an area of research that has received strong interest from academics, industry, and regulators. Despite thi…
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
Adel Javanmard, Rudrajit Das, Alessandro Epasto +1
Retraining a model using its own predictions together with the original, potentially noisy labels is a well-known strategy for improving the model performance. While prior works ha…
DeepCrossAttention: Supercharging Transformer Residual Connections
Mike Heddes, Adel Javanmard, Kyriakos Axiotis +3
Transformer networks have achieved remarkable success across diverse domains, leveraging a variety of architectural innovations, including residual connections. However, traditiona…