research
∙
06/19/2023
An Isotonic Mechanism for Overlapping Ownership
This paper extends the Isotonic Mechanism from the single-owner to multi...
share
research
∙
05/25/2023
Ghost in the Minecraft: Generally Capable Agents for Open-World Enviroments via Large Language Models with Text-based Knowledge and Memory
The captivating realm of Minecraft has attracted substantial research in...
research
∙
11/17/2022
Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information
To effectively exploit the potential of large-scale models, various pre-...
research
∙
07/06/2022
When does SGD favor flat minima? A quantitative characterization via linear stability
The observation that stochastic gradient descent (SGD) favors flat minim...
research
∙
10/08/2020
Deformable DETR: Deformable Transformers for End-to-End Object Detection
DETR has been recently proposed to eliminate the need for many hand-desi...
research
∙
08/06/2020
Benign Overfitting and Noisy Features
Modern machine learning often operates in the regime where the number of...
research
∙
10/18/2019
Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic
This paper proposes SplitSGD, a new stochastic optimization algorithm wi...
research
∙
08/22/2019
VL-BERT: Pre-training of Generic Visual-Linguistic Representations
We introduce a new pre-trainable generic representation for visual-lingu...
research
∙
07/17/2019
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
SLOPE is a relatively new convex optimization procedure for high-dimensi...
research
∙
06/11/2019
Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks
With the widespread success of deep neural networks in science and techn...
research
∙
02/13/2018
Statistical Inference for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent
Stochastic gradient descent (SGD) is an immensely popular approach for o...
research
∙
12/20/2017
Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients
Modern statistical inference tasks often require iterative optimization ...
research
∙
08/10/2017
When Does the First Spurious Variable Get Selected by Sequential Regression Procedures?
Applied statisticians use sequential regression procedures to produce a ...
research
∙
11/12/2015
Private False Discovery Rate Control
We provide the first differentially private algorithms for controlling t...
research
∙
11/05/2015
False Discoveries Occur Early on the Lasso Path
In regression settings where explanatory variables have very low correla...
research
∙
06/17/2015
Communication-Efficient False Discovery Rate Control via Knockoff Aggregation
The false discovery rate (FDR)---the expected fraction of spurious disco...
research
∙
03/04/2015