44 citations · 67 across the 5 of their papers we have counts for
4 papers · 1 filter
Differentiable Implicit Layers
Andreas Look, Simona Doneva, Melih Kandemir +2
In this paper, we introduce an efficient backpropagation scheme for non-constrained implicit functions. These functions are parametrized by a set of learnable weights and may optio…
Dynamic Parameter Allocation in Parameter Servers
Alexander Renz-Wieland, Rainer Gemulla, Steffen Zeuch +1
To keep up with increasing dataset sizes and model complexity, distributed training has become a necessity for large machine learning tasks. Parameter servers ease the implementati…
A Relational Tucker Decomposition for Multi-Relational Link Prediction
Yanjie Wang, Samuel Broscheit, Rainer Gemulla
We propose the Relational Tucker3 (RT) decomposition for multi-relational link prediction in knowledge graphs. We show that many existing knowledge graph embedding models are speci…
On Multi-Relational Link Prediction with Bilinear Models
Yanjie Wang, Rainer Gemulla, Hui Li
We study bilinear embedding models for the task of multi-relational link prediction and knowledge graph completion. Bilinear models belong to the most basic models for this task, t…