32 citations · 45 across the 5 of their papers we have counts for
5 papers
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
Xinyan Dai, Xiao Yan, Kaiwen Zhou +4
The high cost of communicating gradients is a major bottleneck for federated learning, as the bandwidth of the participating user devices is limited. Existing gradient compression…
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search
Xinyan Dai, Xiao Yan, Kelvin K. W. Ng +2
Vector quantization (VQ) techniques are widely used in similarity search for data compression, fast metric computation and etc. Originally designed for Euclidean distance, existing…
Pyramid: A General Framework for Distributed Similarity Search
Shiyuan Deng, Xiao Yan, Kelvin K. W. Ng +2
Similarity search is a core component in various applications such as image matching, product recommendation and low-shot classification. However, single machine solutions are usua…
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou +3
In this paper, we propose a novel sufficient decrease technique for stochastic variance reduced gradient descent methods such as SVRG and SAGA. In order to make sufficient decrease…
Guaranteed Sufficient Decrease for Variance Reduced Stochastic Gradient Descent
Fanhua Shang, Yuanyuan Liu, James Cheng +2
In this paper, we propose a novel sufficient decrease technique for variance reduced stochastic gradient descent methods such as SAG, SVRG and SAGA. In order to make sufficient dec…