| Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance | 0 | 0.34 | 2022 |
| Hyperbolic Neural Networks: Theory, Architectures and Applications | 0 | 0.34 | 2022 |
| Learning Backward Compatible Embeddings | 0 | 0.34 | 2022 |
| Learning with Little Data: Industry Challenges and Innovations | 0 | 0.34 | 2021 |
| Finding Needles In Heterogeneous Haystacks | 0 | 0.34 | 2021 |
| Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs | 0 | 0.34 | 2021 |
| Workshop on Data-Efficient Machine Learning (DeMaL) | 0 | 0.34 | 2021 |
| Bipartite Dynamic Representations for Abuse Detection | 1 | 0.40 | 2021 |
| Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms. | 1 | 0.35 | 2020 |
| Identifying Facet Mismatches In Search Via Micrographs | 0 | 0.34 | 2019 |
| A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews. | 3 | 0.37 | 2018 |
| Dynamic Word Embeddings for Evolving Semantic Discovery. | 11 | 0.76 | 2018 |
| Matrix Factorization with Side and Higher Order Information. | 0 | 0.34 | 2017 |
| On Learning High Dimensional Structured Single Index Models | 1 | 0.35 | 2017 |
| Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction. | 2 | 0.37 | 2016 |
| Classification With the Sparse Group Lasso | 11 | 0.68 | 2016 |
| Structured Sparse Regression via Greedy Hard-Thresholding. | 4 | 0.43 | 2016 |
| On Learning High Dimensional Structured Single Index Models. | 2 | 0.39 | 2016 |
| Goal-Directed Inductive Matrix Completion | 13 | 0.58 | 2016 |
| Learning Single Index Models in High Dimensions | 6 | 0.60 | 2015 |
| PU matrix completion with graph information | 0 | 0.34 | 2015 |
| Sparse and Low-Rank Tensor Decomposition | 2 | 0.36 | 2015 |
| Optimal Low-Rank Tensor Recovery from Separable Measurements: Four Contractions Suffice | 4 | 0.40 | 2015 |
| Collaborative Filtering with Graph Information: Consistency and Scalable Methods | 25 | 0.80 | 2015 |
| Forward - Backward greedy algorithms for signal demixing. | 1 | 0.36 | 2014 |
| Logistic Regression with Structured Sparsity. | 0 | 0.34 | 2014 |
| Forward - Backward Greedy Algorithms for Atomic Norm Regularization. | 1 | 0.34 | 2014 |
| A greedy forward-backward algorithm for atomic norm constrained minimization | 7 | 0.49 | 2013 |
| Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI Analysis. | 12 | 0.59 | 2013 |
| Universal Measurement Bounds for Structured Sparse Signal Recovery | 0 | 0.34 | 2012 |
| Universal Measurement Bounds for Structured Sparse Signal Recovery. | 26 | 0.99 | 2012 |
| Convex Approaches To Model Wavelet Sparsity Patterns | 37 | 1.49 | 2011 |
| Tight Measurement Bounds for Exact Recovery of Structured Sparse Signals | 8 | 0.59 | 2011 |
