research
∙
09/18/2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
In this work, we present a scalable reinforcement learning method for tr...
share
research
∙
08/22/2023
Inferring gender from name: a large scale performance evaluation study
A person's gender is a crucial piece of information when performing rese...
research
∙
08/10/2023
RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model
Inspired by the recent success of large language models (LLMs) like Chat...
research
∙
07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
research
∙
06/28/2023
Event Detection from Social Media Stream: Methods, Datasets and Opportunities
Social media streams contain large and diverse amount of information, ra...
research
∙
05/17/2023
Exploring Inductive Biases in Contrastive Learning: A Clustering Perspective
This paper investigates the differences in data organization between con...
research
∙
05/05/2023
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
We describe a system for deep reinforcement learning of robotic manipula...
research
∙
04/04/2023
Spatiotemporal and Semantic Zero-inflated Urban Anomaly Prediction
Urban anomaly predictions, such as traffic accident prediction and crime...
research
∙
03/14/2023
Sr-init: An interpretable layer pruning method
Despite the popularization of deep neural networks (DNNs) in many fields...
research
∙
03/02/2023
Open-World Object Manipulation using Pre-trained Vision-Language Models
For robots to follow instructions from people, they must be able to conn...
research
∙
03/01/2023
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control
Recent progress in large language models (LLMs) has demonstrated the abi...
research
∙
12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
research
∙
11/16/2022
Token Turing Machines
We propose Token Turing Machines (TTM), a sequential, autoregressive Tra...
research
∙
11/16/2022
Egocentric Hand-object Interaction Detection
In this paper, we propose a method to jointly determine the status of ha...
research
∙
10/19/2022
Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization
We propose a framework to enable multipurpose assistive mobile robots to...
research
∙
10/15/2022
PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale
The predictive information, the mutual information between the past and ...
research
∙
10/08/2022
Low Error-Rate Approximate Multiplier Design for DNNs with Hardware-Driven Co-Optimization
In this paper, two approximate 3*3 multipliers are proposed and the synt...
research
∙
08/16/2022
The least-used key selection method for information retrieval in large-scale Cloud-based service repositories
As the number of devices connected to the Internet of Things (IoT) incre...
research
∙
05/10/2022
Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures
With the advent of ubiquitous deployment of smart devices and the Intern...
research
∙
04/05/2022
Jump-Start Reinforcement Learning
Reinforcement learning (RL) provides a theoretical framework for continu...
research
∙
04/04/2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Large language models can encode a wealth of semantic knowledge about th...
research
∙
02/02/2022
On-Sensor Binarized Fully Convolutional Neural Network with A Pixel Processor Array
This work presents a method to implement fully convolutional neural netw...
research
∙
01/20/2022
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks
We propose an optimization method for the automatic design of approximat...
research
∙
01/02/2022
Detail-Preserving Transformer for Light Field Image Super-Resolution
Recently, numerous algorithms have been developed to tackle the problem ...
research
∙
01/02/2022
Optimizing Machine Learning Inference Queries with Correlative Proxy Models
We consider accelerating machine learning (ML) inference queries on unst...
research
∙
11/24/2021
Graph Modularity: Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks
There are good arguments to support the claim that feature representatio...
research
∙
11/22/2021
Graph-Based Similarity of Neural Network Representations
Understanding the black-box representations in Deep Neural Networks (DNN...
research
∙
11/09/2021
AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale
Robotic skills can be learned via imitation learning (IL) using user-pro...
research
∙
11/04/2021
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning
Reinforcement learning can train policies that effectively perform compl...
research
∙
10/28/2021
RGP: Neural Network Pruning through Its Regular Graph Structure
Lightweight model design has become an important direction in the applic...
research
∙
09/29/2021
The Object at Hand: Automated Editing for Mixed Reality Video Guidance from Hand-Object Interactions
In this paper, we concern with the problem of how to automatically extra...
research
∙
09/29/2021
Egocentric Hand-object Interaction Detection and Application
In this paper, we present a method to detect the hand-object interaction...
research
∙
09/29/2021
Understanding Egocentric Hand-Object Interactions from Hand Pose Estimation
In this paper, we address the problem of estimating the hand pose from t...
research
∙
08/05/2021
Q-error Bounds of Random Uniform Sampling for Cardinality Estimation
Random uniform sampling has been studied in various statistical tasks bu...
research
∙
07/22/2021
Deep 3D-CNN for Depression Diagnosis with Facial Video Recording of Self-Rating Depression Scale Questionnaire
The Self-Rating Depression Scale (SDS) questionnaire is commonly utilize...
research
∙
07/20/2021
S2Looking: A Satellite Side-Looking Dataset for Building Change Detection
Collecting large-scale annotated satellite imagery datasets is essential...
research
∙
06/08/2021
Optimization of Service Addition in Multilevel Index Model for Edge Computing
With the development of Edge Computing and Artificial Intelligence (AI) ...
research
∙
05/03/2021
ISTR: End-to-End Instance Segmentation with Transformers
End-to-end paradigms significantly improve the accuracy of various deep-...
research
∙
04/18/2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
When primed with only a handful of training samples, very large pretrain...
research
∙
04/15/2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
We consider the problem of learning useful robotic skills from previousl...
research
∙
04/06/2021
Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning
Detection and localization of actions in videos is an important problem ...
research
∙
04/06/2021
Learning to Estimate Hidden Motions with Global Motion Aggregation
Occlusions pose a significant challenge to optical flow algorithms that ...
research
∙
04/05/2021
Learning Optical Flow from a Few Matches
State-of-the-art neural network models for optical flow estimation requi...
research
∙
03/26/2021
Visionary: Vision architecture discovery for robot learning
We propose a vision-based architecture search algorithm for robot manipu...
research
∙
10/27/2020
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Multi-document summarization is a challenging task for which there exist...
research
∙
08/24/2020
Approximate Partition Selection for Big-Data Workloads using Summary Statistics
Many big-data clusters store data in large partitions that support acces...
research
∙
08/06/2020
Gathering GitHub OSS Requirements from Q A Community: an Empirical Study
Cross-community collaboration can exploit the expertise and knowledges o...
research
∙
06/24/2020
Disentangle Perceptual Learning through Online Contrastive Learning
Pursuing realistic results according to human visual perception is the c...
research
∙
06/22/2020
Bidirectional Self-Normalizing Neural Networks
The problem of exploding and vanishing gradients has been a long-standin...
research
∙
05/14/2020