Master's Theses & Technical Reports - Joseph Gonzalez

5th Year M.S. | M.S.

5th Year M.S.

Cloudless and Mixclaves
Vikranth Srivatsa [2023]

Contrastive Learning for Combinatorial Optimization
Mohamed Elgharbawy [2023]

Embeddings for Optimization Modulo Theories Learned by Graph Neural Network Guided Solvers are Robust to Logical Space Perturbations
Chirag Sharma [2023]

Improve Model Inference Cost with Image Gridding
Shreyas Krishnaswamy [2023]

LoopNeRF: Exploring Temporal Compression for 3D Video Textures
Alexander Kristoffersen [2023]

ShengJi+: Playing Tractor with Deep Reinforcement Learning
Jerry Shan [2023]

A Study of Generalization Metrics for Natural Language Processing: Correlational Analysis and a Simpson's Paradox
Raguvir Kunani [2022]

Bridging the Gap Between Modular and End-to-end Autonomous Driving Systems
Eric Leong [2022]

FogROS: An Adaptive Framework for Automating Fog Robotics Deployment and Co-scheduling Feature Updates and Queries for Feature Stores
Yafei Liang [2022]

Knowledge-Guided Self-Supervised Vision Transformers for Medical Imaging
Kevin Miao [2022]

Low-Rank and Temporal Smoothness Regularization on Value-Based Deep Reinforcement Learning
Edward Yam [2022]

Making the Most of Serverless Accelerators
Aditya Ramkumar [2022]

Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly
Vedaad Shakib [2022]

The Effect of Model Size on Worst-Group Generalization
Alan Pham [2022]

Extremely Lightweight Vocoders for On-device Speech Synthesis
Tianren Gao [2021]

Fast Low-Overhead Logging Extending Time
Anusha Dandamudi [2021]

Masked Layer Distillation: Fast and Robust Training Through Knowledge Transfer Normalization
Derek Wan [2021]

You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module
Bohan Zhai [2021]

A Study of Transfer Learning Methods within Natural Language Processing and Reinforcement Learning
Shrishti Jeswani [2020]

Adaptive Text-to-Speech in Low Computational Resource Scenarios
Flora Xue [2020]

Challenges and Tradeoffs in Trajectory Prediction for Autonomous Driving
Alvin Kao [2020]

Communication-Efficient Federated Learning with Sketching
Ashwinee Panda [2020]

Dynamic Deadlines in Motion Planning for Autonomous Driving Systems
Edward Fang [2020]

Efficient Distribution of Robotics Workloads using Fog Computing
Raghav Anand [2020]

Interpretable Few-Shot Image Classification with Neural-Backed Decision Trees
Scott Lee [2020]

Micro-Domain Adaptation on Long-Running Videos
Victor Sun [2020]

Multi-Task Learning Architectures and Applications
Andy Yan [2020]

NBDT: Neural-Backed Decision Trees
Daniel Ho [2020]

Object Tracking for Autonomous Driving Systems
Aman Dhar [2020]

Scoring Confidence in Neural Networks
Nikita Vemuri [2020]

Using Dataflow for Machine Learning Inference
Harikaran Subbaraj [2020]

Time Constraints and Fault Tolerance in Autonomous Driving Systems
Yujia Luo [2019]

Epigenetic Imputation
Alexander Ku [2018]

InferLine: ML Inference Pipeline Composition Framework
Corey Zumar [2018]


Ansor: Generating High-Performance Tensor Programs for Deep Learning
Lianmin Zheng [2021]

Learning Self-Supervised Representations of Code Functionality
Paras Jain [2021]

Efficient Inference on Video, In Real-Time and At Scale
Samvit Jain [2019]

Efficient Inference on Video, In Real-Time and At Scale
Samvit Jain [2019]

Efficient Inference on Video, In Real-Time and At Scale
Samvit Jain [2019]