Questions tagged [papers]

For questions related to artificial intelligence research papers. So, you should use this tag if you want someone to clarify something in a research paper.

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6
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1answer
85 views

How does the network know which objects to track in the paper “Label-Free Supervision of Neural Networks with Physics and Domain Knowledge”?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...
5
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0answers
99 views

Wasserstein GAN: Implemention of Critic Loss Correct?

The WGAN paper concretely proposes Algorithm 1 (cf. page 8). Now, they also state what their loss for the critic and the generator is. When implementing the critic loss (so lines 5 and 6 of Algorithm ...
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0answers
48 views

Visualizing the Loss Landscape of Neural Nets: Meaning of the word 'filter'?

I found myself scratching my head when I read the following phrase in the paper Visualizing the Loss Landscape of Neural Nets: To remove this scaling effect, we plot loss functions using filter-wise ...
4
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0answers
94 views

$\frac{P(x_1 \mid y, s = 1) \dots P(x_n \mid y, s = 1) P(y \mid s = 1)}{P(x \mid s = 1)}$ indicates that naive Bayes learners are global learners?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3. Learning under sample selection bias, the author says the following: ...
4
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0answers
236 views

Why does the BERT encoder have an intermediate layer between the attention and neural network layers with a bigger output?

I am reading the BERT paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. As I look at the attention mechanism, I don't understand why in the BERT encoder we have ...
3
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0answers
28 views

What's up with Neural Stochastic Differential Equations from a practical standpoint?

I've spent a few days reading some of the new papers about Neural SDEs. For example, here is one from Tzen and Raginsky and here is one that came out simultaneously by Peluchetti and Favaro. There are ...
3
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0answers
53 views

Why is it necessary to divide the priority range according to the batch size in Prioritized Experience Replay?

According to DeepMinds's paper Prioritized Experience Replay (2016), specifically Appendix B.2.1 "Proportional prioritization" (p. 13), one should equally divide the priority range $[0, p_\...
3
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1answer
85 views

How are the “Link Strength true”, “Link Strength blind” and “Mutual Information” calculated in this report on Bayesian networks?

I'm trying to understand how to calculate the strength of every arc in a Bayesian Network. I came across this report Measuring Connection Strengths and Link Strengths in Discrete Bayesian Networks, ...
3
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153 views

Understanding the results of “Visualizing and Understanding Convolutional Networks”

I am trying to understand the results of the paper Visualizing and Understanding Convolutional Networks, in particular the following image: What are these 3x3 blocks and their 9 cells representing? ...
3
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114 views

How is the state-visitation frequency computed in “Maximum Entropy Inverse Reinforcement Learning”?

I am trying to understand the formulation of the maximum entropy Inverse RL method by Brian Ziebart. Particularly, I am stuck on how to understand the computation of state - visitation frequencies. ...
3
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1answer
114 views

Understanding proof of lemma 1 (policy improvement bound) of the “Trust Region Policy Optimization” paper

In the Trust Region Policy Optimization paper, in Lemma 1 of Appendix A, I did not quite understand the transition from (21) from (20). In going from (20) to (21), $A^\pi(s_t, a_t)$ is substituted ...
3
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1answer
94 views

How are the observations stored in the RNN that encodes the state?

I am a bit confused about observations in RL systems which use RNN to encode the state. I read a few papers like this and this. If I were to use a sequence of raw observations (or features) as an ...
3
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1answer
368 views

What is the significance of this Stanford University “Financial Market Time Series Prediction with RNN's” paper?

Researchers at Stanford University released, in 2012, the paper Financial Market Time Series Prediction with Recurrent Neural Networks. It goes on to discuss how they used echo state networks to ...
3
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40 views

What is the “question” when using Dynamic Memory Networks to do part-of-speech tagging and sentiment analysis?

In the paper Ask Me Anything: Dynamic Memory Networks for Natural Language Processing the authors described a Dynamic Memory Network in the context of question answering. Then, they also tested the ...
3
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1answer
119 views

How to perform back-propagation in Decoupled Neural Interfaces?

I am attempting to create a fully decoupled feed-forward neural network by using decoupled neural interfaces (DNIs) as explained in the paper Decoupled Neural Interfaces using Synthetic Gradients (...
3
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1answer
79 views

What is meant by “the number of examples is reduced”, and why is this the case?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.2. Logistic Regression, the author says the following: 3.2. Logistic ...
2
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0answers
18 views

What is meant by Hinton when he refers to “Part-Whole Hierarchies” in his GLOM framework

I was recently reading Hinton's GLOM idea How to represent part-whole hierarchies in a neural network, and I am simply unsure about what exactly he means when he says parsing images into "part-...
2
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0answers
36 views

How many papers about AI / ML were published in the recent years?

I am trying to formulate an argument at work saying the disruption in AI/ML is very high and that it is hard to stay "state of the art". I would like to support that hypothesis by numbers. ...
2
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35 views

What is the paper that states that humans incorrectly trust the incorrect explanations of the AI?

I was reading a paper on the subject of explainable AI and interpretability, in particular the tendency of people (even experts) to excessively trusting explanations given by AI. In the intro the ...
2
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0answers
57 views

What is the dimensionality of these derivatives in the paper “Active Learning for Reward Estimation in Inverse Reinforcement Learning”?

I'm trying to implement in code part of the following paper: Active Learning for Reward Estimation in Inverse Reinforcement Learning. I'm specifically referring to section 2.3 of the paper. Let's ...
2
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0answers
23 views

Is it possible to ensure the convergence when training a RNN weight on its SVD decomposition?

I'm reading the following paper in which the author seems to do 2 things interesting: The hidden-to-hidden weight matrix of the RNN is SVD decomposed and train separately. Each orthogonal part of the ...
2
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0answers
46 views

How does the support vector machine constraint imply that sample selection bias will not systematically affect the output of the optimisation?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.4. Support vector machines, the author says the following: 3.4. ...
2
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0answers
34 views

How are the lower and upper bound values of the moths determined in the Moth-Flame Optimization algorithm?

I am currently implementing the Moth-Flame Optimization (MFO) Algorithm, based on the paper: Moth-Flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm. To calculate the values of ...
2
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0answers
90 views

What is the purpose of the DAMSM loss for the generators in AttnGAN?

I am confused about the training part in AttnGan. If you observe page 3. There are two types of losses for generator network: one involving the Deep Attentional Multimodal Similarity Model (DAMSM) ...
2
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0answers
94 views

What is the memory complexity of the memory-efficient attention in Reformer?

When I read the paper, Reformer: The Efficient Transformer, I cannot get the same complexity of the memory-efficient method in Table 1 (p. 5), which summarizes time/memory complexity of scaled dot-...
2
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0answers
49 views

What is meant by “arranging the final features of CNN in a grid” and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...
2
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0answers
137 views

Ways to keep up with the latest developments in Machine Learning and AI?

With over 100 papers published in the area of artificial intelligence, machine learning and their subfields every day (source), accounting for ~3% of all publications world wide per year (source) and ...
2
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1answer
70 views

What is a heatmap in the CornerNet paper?

I have been working on understanding how CornerNet works, but I couldn't figure out a few parts about the architecture. First, the authors mention that there are 3 distinct parts to be predicted as a ...
2
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0answers
25 views

Deriving hyperparameter updates in Online Interactive Collaborative Filtering

I've been going through "Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms" by Wang et al. and am unable to understand how the update equations for the ...
2
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0answers
47 views

Are the final states not being updated in this $n$-step Q-Learning algorithm?

I am reading this paper and in algorithm 3 they describe an $n$-step Q-Learning algorithm. Below is the pseudo-code. From this pseudo-code, it looks as though the final tuples that they would ...
2
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0answers
54 views

How are the classical MDP and the object-oriented MDP views different?

I've been reading the attached paper - which aims to model entities in the world as objects, including the learning agent itself! To say the least, the goal is to navigate through what seems like a ...
2
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0answers
57 views

Do I have to downsample the input and upsample the output of the neural network when implementing the NICE algorithm?

Consider that my input is an RGB image. The size of my image is $N\times N$. I'm trying to implement NICE algorithm presented by Dinh. The bijective function $f: \mathbb{R}^d \to \mathbb{R}^d$ maps $X$...
2
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0answers
79 views

Why does GAN loss converge to log(2) and not -log(2)?

In Goodfellow's paper, he says: Hence, by inspecting Eq. 4 at $D^*_G (\mathbf{x}) = \frac{1}{2}$, we find $C(G) = \log \frac{1}{2}+ \log \frac{1}{2} = − \log 4$. To see that this is the best ...
2
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0answers
41 views

How can I get to a final output of shape $224 \times 224$, without FC layers, from a tensor of specific shape, in OpenPose?

I am approaching the implementation of the OpenPose algorithm for realtime human body pose estimation. According to the official paper OpenPose: Realtime Multi-Person 2D Pose Estimation using Part ...
2
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0answers
45 views

Recent algorithms for correcting mislabeled data using multilayer perceptrons

I am doing literature research on algorithms for correcting mislabeled data using multilayer perceptrons. Found an "old" paper An algorithm for correcting mislabeled data (2001) by Xinchuan Zeng et al....
2
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0answers
40 views

How is the gradient with respect to weights derived in batch normalization?

This is a cross-post, as I didn't get any answers on Stats SE and I am hoping that it gets more attention here. At the bottom of page 2 of the paper L2 Regularization versus Batch and Weight ...
2
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0answers
39 views

Why is this Monte Carlo approach scalable for a growing number of states variables and action variables?

I am reading a research paper on the formulation of MDP problems to ICU treatment decision making: Treatment Recommendation in Critical Care: A Scalable and Interpretable Approach in Partially ...
2
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0answers
36 views

YOLO 9000 about Better Stronger

In this paper, YOLO has three features compared to YOLO v1. This question is about Better and Faster. In the Better section, there are many techniques such as Batch Norm, Anchor Box and so on. In the ...
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0answers
66 views

What is the difference between Squeeze-and-excite and bottleneck modules from Mobilenet v2?

Squezee-and-excite networks introduced SE blocks, while MobileNet v2 introduced linear bottlenecks. What is the effective difference between these two concepts? Is it only implementation (depth-wise ...
2
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0answers
88 views

Infinite horizon in Reinforcement Learning

I read this article: "Towards Autonomous Data Ferry Route Design through Reinforcement Learning" by Daniel Henkel and Timothy X Brown. It specifies an infinite horizon problem where they use as a ...
2
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0answers
12 views

How do we stack two U-Nets to yield one final prediction?

I am trying to reproduce the model described in the paper DocUNet: Document Image Unwarping via A Stacked U-Net, i.e. stacking two U-Nets to yield one final prediction. The paper mentions that: ...
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0answers
12 views

What's mutual exclusivity in meta-learning?

What do we mean by mutual exclusivity of tasks? This work (E Pan, 21) and this one (M Yin, 20) state that most classification meta-learning algorithms fail for non-mutually exclusive tasks as the ...
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0answers
27 views

What is a Hebbian linear classifier?

I was reading Deep Learning of Representations for Unsupervised and Transfer Learning, and they state the following: They have only a small number of unlabeled examples (4096) and very few labeled ...
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0answers
17 views

Clonal operator in Immune Clonal Strategy

I was reading about Immune Clonal Strategy, specifically about Monoclonal operator from Immunity clonal strategies, and it goes as follows: Here $a_i $ is a point and $a_i = \{ x_1, x_2, \cdots, x_m \...
1
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0answers
23 views

What is the meaning of “Our current objective weights every token equally and lacks a notion of what is most important to predict” in the GPT-3 paper?

On page 34 of OpenAI's GPT-3, there is a sentence demonstrating the limitation of objective function: Our current objective weights every token equally and lacks a notion of what is most important to ...
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0answers
25 views

The MLP output of a neural network can be written as $\|x\|\|w_l\|\cos(\theta_l)$: why is the norm easier to maximize?

The MLP output of a neural network is a dot product between the weights and the input and therefore can be written as $\|x\|\|w_l\|\cos(\theta_l)$ (see this for more details), where $x$ is the input, $...
1
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1answer
52 views

Is there a full and precise formulation of Theorem 1 in the Integrated Gradients paper?

Theorem 1 (page 5) in the paper about Integrated Gradients states that Integrated gradients is the unique path method that is symmetry-preserving. What I miss is A precise formulation of the ...
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0answers
51 views

BlackOut - ICLR 2016: need help understanding the cost function derivative

In the ICLR 2016 paper BlackOut: Speeding up Recurrent Neural Network Language Models with very Large Vocabularies, on page 3, for eq. 4: $$ J_{ml}^s(\theta) = log \ p_{\theta}(w_i | s) $$ They have ...
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0answers
29 views

Is the framework provided by this paper for checking the constraints of AI systems really new?

The authors of this paper present a framework for checking the constraints of AI systems using formal argumentative logic between 2 agents: an interrogating agent and a suspect agent. The ...
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0answers
18 views

Why does the relativistic discriminator increase the probability that generated data are real and decrease the probability that real data are real?

I was reading the ESRGAN whitepaper, where I came across this line: Relativistic discriminator [2] is developed not only to increase the probability that generated data are real but also to ...