11 citations · 16 across the 11 of their papers we have counts for
11 papers
DUET -- Dual User Embedding Transformers for Offsite Conversion Prediction
Reazul Hasan Russel, Mingwei Tang, Rostam Shirani +18
Offsite conversion rate (OCVR) prediction is an important ranking problem in computational recommendation systems. This task presents a modeling challenge: click signals are abunda…
Does Few-Shot Learning Help LLM Performance in Code Synthesis?
Derek Xu, Tong Xie, Botao Xia +4
Large language models (LLMs) have made significant strides at code generation through improved model design, training, and chain-of-thought. However, prompt-level optimizations rem…
Inverse designing metamaterials with programmable nonlinear functional responses in graph space
Marco Maurizi, Derek Xu, Yu-Tong Wang +9
Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, an…
Mixture of In-Context Prompters for Tabular PFNs
Derek Xu, Olcay Cirit, Reza Asadi +2
Recent benchmarks found In-Context Learning (ICL) outperforms both deep learning and tree-based algorithms on small tabular datasets. However, on larger datasets, ICL for tabular l…
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data
Wei-Yao Wang, Wei-Wei Du, Derek Xu +2
Self-supervised learning (SSL) has been incorporated into many state-of-the-art models in various domains, where SSL defines pretext tasks based on unlabeled datasets to learn cont…
Unveiling Invariances via Neural Network Pruning
Derek Xu, Yizhou Sun, Wei Wang
Invariance describes transformations that do not alter data's underlying semantics. Neural networks that preserve natural invariance capture good inductive biases and achieve super…
Introducing Semantics into Speech Encoders
Derek Xu, Shuyan Dong, Changhan Wang +10
Recent studies find existing self-supervised speech encoders contain primarily acoustic rather than semantic information. As a result, pipelined supervised automatic speech recogni…
Detecting Small Query Graphs in A Large Graph via Neural Subgraph Search
Yunsheng Bai, Derek Xu, Yizhou Sun +1
Recent advances have shown the success of using reinforcement learning and search to solve NP-hard graph-related tasks, such as Traveling Salesman Optimization, Graph Edit Distance…
FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2
Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan +12
Mobility, power, and price points often dictate that robots do not have sufficient computing power on board to run contemporary robot algorithms at desired rates. Cloud computing p…
Ray Based Distributed Autonomous Vehicle Research Platform
Derek Xu
My project tackles the question of whether Ray can be used to quickly train autonomous vehicles using a simulator (Carla), and whether a platform robust enough for further research…
GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun +1
Detecting the Maximum Common Subgraph (MCS) between two input graphs is fundamental for applications in drug synthesis, malware detection, cloud computing, etc. However, MCS comput…