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Found 14 papers, 3 papers with code
Estimation for conditional moment models based on martingale difference divergence
To overcome this identification issue, we further provide a two-step estimation procedure for the model with intercept parameters.
Self-Supervised Visual Preference Alignment
We generate chosen and rejected responses with regard to the original and augmented image pairs, and conduct preference alignment with direct preference optimization.
Ranked #31 on
Visual Question Answering
on MM-Vet
DiffuLT: How to Make Diffusion Model Useful for Long-tail Recognition
This paper proposes a new pipeline for long-tail (LT) recognition.
Low-rank Attention Side-Tuning for Parameter-Efficient Fine-Tuning
Because learnable parameters from these methods are entangled with the pretrained model, gradients related to the frozen pretrained model's parameters have to be computed and stored during finetuning.
Rectify the Regression Bias in Long-Tailed Object Detection
While existing methods fail to handle the regression bias, the class-specific regression head for rare classes is hypothesized to be the main cause of it in this paper.
DTL: Disentangled Transfer Learning for Visual Recognition
When pre-trained models become rapidly larger, the cost of fine-tuning on downstream tasks steadily increases, too.
Multi-Label Self-Supervised Learning with Scene Images
Self-supervised learning (SSL) methods targeting scene images have seen a rapid growth recently, and they mostly rely on either a dedicated dense matching mechanism or a costly unsupervised object discovery module.
Quantized Feature Distillation for Network Quantization
QFD first trains a quantized (or binarized) representation as the teacher, then quantize the network using knowledge distillation (KD).
Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images
That is, coarse crops benefits scene images SSL.
Instance-based Max-margin for Practical Few-shot Recognition
With both the new pFSL setting and novel IbM2 method, this paper shows that practical few-shot learning is both viable and promising.
Big portfolio selection by graph-based conditional moments method
Next, the GRACE method learns the conditional variance, skewness, and kurtosis of stock returns from the learned conditional quantiles by using the quantiled conditional moment (QCM) method.
Statistical inference for the logarithmic spatial heteroskedasticity model with exogenous variables
For the log-SHE model, its spatial near-epoch dependence (NED) property is investigated, and a systematic statistical inference procedure is provided, including the maximum likelihood and generalized method of moments estimators, the Wald, Lagrange multiplier and likelihood-ratio-type D tests for model parameter constraints, and the overidentification test for the model diagnostic checking.
Residual Attention: A Simple but Effective Method for Multi-Label Recognition
Multi-label image recognition is a challenging computer vision task of practical use.
Ranked #1 on
Multi-Label Image Classification
on VOC2007
Path-specific Effects Based on Information Accounts of Causality
Path-specific effects in mediation analysis provide a useful tool for fairness analysis, which is mostly based on nested counterfactuals.
