Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Inference for Large Scale Image Classification   Bayesian inference promises to ground and improve the performance of deep
neural networks. It promises to be robust to overfitting, to simplify the
training procedure and the space of hyperparameters, and to provide a
calibrated measure of uncertainty that can enhance decision making, agent
exploration and prediction fairness. Markov Chain Monte Carlo (MCMC) methods
enable Bayesian inference by generating samples from the posterior distribution
over model parameters. Despite the theoretical advantages of Bayesian inference
and the similarity between MCMC and optimization methods, the performance of
sampling methods has so far lagged behind optimization methods for large scale
deep learning tasks. We aim to fill this gap and introduce ATMC, an adaptive
noise MCMC algorithm that estimates and is able to sample from the posterior of
a neural network. ATMC dynamically adjusts the amount of momentum and noise
applied to each parameter update in order to compensate for the use of
stochastic gradients. We use a ResNet architecture without batch normalization
to test ATMC on the Cifar10 benchmark and the large scale ImageNet benchmark
and show that, despite the absence of batch normalization, ATMC outperforms a
strong optimization baseline in terms of both classification accuracy and test
log-likelihood. We show that ATMC is intrinsically robust to overfitting on the
training data and that ATMC provides a better calibrated measure of uncertainty
compared to the optimization baseline.

29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
36
The categories of this paper are: cmp-lg