2 citations · 8 across the 9 of their papers we have counts for
9 papers
Fast Heavy Inner Product Identification Between Weights and Inputs in Neural Network Training
Lianke Qin, Saayan Mitra, Zhao Song +2
In this paper, we consider a heavy inner product identification problem, which generalizes the Light Bulb problem~(\cite{prr89}): Given two sets and $B \sub…
Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Lianke Qin, Zhao Song, Baocheng Sun
A rising trend in theoretical deep learning is to understand why deep learning works through Neural Tangent Kernel (NTK) [jgh18], a kernel method that is equivalent to using gradie…
Online Adaptive Mahalanobis Distance Estimation
Lianke Qin, Aravind Reddy, Zhao Song
Mahalanobis metrics are widely used in machine learning in conjunction with methods like -nearest neighbors, -means clustering, and -medians clustering. Despite their impo…
Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification
Lianke Qin, Zhao Song, Yuanyuan Yang
Deep learning has been widely used in many fields, but the model training process usually consumes massive computational resources and time. Therefore, designing an efficient neura…
Toward Highly Efficient and Private Submodular Maximization via Matrix-Based Acceleration
Boyu Liu, Lianke Qin, Zhao Song +2
Submodular function maximization is a critical building block for diverse tasks, such as document summarization, sensor placement, and image segmentation. Yet its practical utility…
A General Algorithm for Solving Rank-one Matrix Sensing
Lianke Qin, Zhao Song, Ruizhe Zhang
Matrix sensing has many real-world applications in science and engineering, such as system control, distance embedding, and computer vision. The goal of matrix sensing is to recove…
Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations
Lianke Qin, Aravind Reddy, Zhao Song +2
In this paper, we propose Adam-Hash: an adaptive and dynamic multi-resolution hashing data-structure for fast pairwise summation estimation. Given a data-set $X \subset \mathbb{R}^…
Adore: Differentially Oblivious Relational Database Operators
Lianke Qin, Rajesh Jayaram, Elaine Shi +3
There has been a recent effort in applying differential privacy on memory access patterns to enhance data privacy. This is called differential obliviousness. Differential oblivious…
A Sublinear Adversarial Training Algorithm
Yeqi Gao, Lianke Qin, Zhao Song +1
Adversarial training is a widely used strategy for making neural networks resistant to adversarial perturbations. For a neural network of width , input training data in …