Search Results for author:
Found 7 papers, 1 papers with code
Accurate estimation of feature importance faithfulness for tree models
In this paper, we consider a perturbation-based metric of predictive faithfulness of feature rankings (or attributions) that we call PGI squared.
Scaling Laws for Fine-Grained Mixture of Experts
Our findings not only show that MoE models consistently outperform dense Transformers but also highlight that the efficiency gap between dense and MoE models widens as we scale up the model size and training budget.
Contrastive News and Social Media Linking using BERT for Articles and Tweets across Dual Platforms
Inspired by the success of the CLIP model in computer vision, which employs contrastive learning to model similarities between images and captions, this paper introduces a contrastive learning approach for training a representation space where linked articles and tweets exhibit proximity.
Improving Ads-Profitability Using Traffic-Fingerprints
This paper introduces the concept of traffic-fingerprints, i. e., normalized 24-dimensional vectors representing a distribution of daily traffic on a web page.
Improved Feature Importance Computations for Tree Models: Shapley vs. Banzhaf
Using the computational techniques developed for Shapley values we deliver an optimal $O(TL+n)$ time algorithm for computing Banzhaf values based explanations.
Decomposable Submodular Function Minimization via Maximum Flow
This paper bridges discrete and continuous optimization approaches for decomposable submodular function minimization, in both the standard and parametric settings.
RecSys Challenge 2016: job recommendations based on preselection of offers and gradient boosting
We present the Mim-Solution's approach to the RecSys Challenge 2016, which ranked 2nd.
