Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Multi-Relational Learning at Scale with ADMM
Distributed Stochastic ADMM for Matrix Factorization
Regularized multi--task learning
Gradient-based boosting for statistical relational learning: The relational dependency network case
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning
ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs.
Integrating low-rank and group-sparse structures for robust multi-task learning
Learning Multi-way Relations via Tensor Decomposition with Neural Networks
Optimization Methods for Large-Scale Machine Learning
Scalable Algorithms for Multi-Instance Learning
Logistic Tensor Factorization for Multi-Relational Data
Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM
On the Convergence of Adam and Beyond
A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning
A Riemannian Network for SPD Matrix Learning
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments
Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems
Exploiting Unrelated Tasks in Multi-Task Learning
Probabilistic Low-Rank Multitask Learning
D-MFVI: Distributed Mean Field Variational Inference using Bregman ADMM
Minimum-time speed optimisation over a fixed path
Autophagy protects human podocytes from high glucose-induced injury by preventing insulin resistance.
ScyPer: elastic OLAP throughput on transactional data
Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification
Algorithms for Non-negative Matrix Factorization