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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18
votes
3answers
4k views

Why do most deep learning papers not include an implementation?

I'm a novice researcher, and as I started to read papers in the area of deep learning I noticed that the implementation is normally not added and is needed to be searched elsewhere, and my question is ...
9
votes
2answers
5k views

Where can I find the original paper that introduced RNNs?

I was able to find the original paper on LSTM, I was not able to find the paper that introduced "vanilla" RNNs. Where can I find it?
6
votes
1answer
153 views

Are there human predictions of when a computer would have been better than a human at Go?

I just stumbled across the paper When Will AI Exceed Human Performance? Evidence from AI Experts, which contains a figure showing the aggregated subjective probability of "high-level machine ...
5
votes
1answer
536 views

What if the more fit parent has fewer nodes compared to the other, will the disjoint and excess genes be discarded?

In the paper Efficient Evolution of Neural Network Topologies (2002), the authors say Genes that do not match are inherited from the more fit parent What if the more fit parent has fewer nodes ...
5
votes
2answers
533 views

Where to publish reasonable article in Deep Reinforcement Learning?

Please, can someone give advice what journals are good for first publication in the field of Deep Reinforcement Learning? I am in process of writing about research results of DQN related algorithms. ...
5
votes
1answer
356 views

What is the “semantic level”?

I am reading the paper Hierarchical Attention-Based Recurrent Highway Networks for Time Series Prediction (2018) by Yunzhe Tao et al. In this paper, they use several times the expression "semantic ...
5
votes
1answer
131 views

Are the ideas in the paper “Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour” novel?

In the paper Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour, the authors seem to be presenting a black box method of testing. Are these ideas really new? Weren't these ...
5
votes
1answer
1k views

How does weight normalization work?

I was reading the paper Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks about improving the learning of an ANN using weight normalization. They ...
4
votes
1answer
61 views

What is the meaning of the square brackets in ant colony optimization?

I'm studying the paper "Minimizing Total Tardiness on a Single Machine Using Ant Colony Optimization" which has proposed to use Ant colony optimization to SMTWTP. According to this paper: Each ...
4
votes
1answer
439 views

What is the meaning of “stationarity of statistics” and “locality of pixel dependencies”?

I'm reading the ImageNet Classification with Deep Convolutional Neural Networks paper by Krizhevsky et al, and came across these lines in the Intro paragraph: Their (convolutional neural networks') ...
4
votes
1answer
78 views

How does the Ornstein-Uhlenbeck process work, and how it is used in DDPG?

In section 3 of the paper Continuous control with deep reinforcement learning, the authors write As detailed in the supplementary materials we used an Ornstein-Uhlenbeck process (Uhlenbeck & ...
4
votes
1answer
67 views

Are the labels updated during training in the algorithm presented in “An algorithm for correcting mislabeled data”?

I am trying to understand an algorithm for correcting mislabeled data in the paper An algorithm for correcting mislabeled data (2001) by Xinchuan Zeng et al. The authors are suggesting to update the ...
4
votes
1answer
195 views

Name of paper for encoding/representing XY coordinates in deep learning

It this podcast between Oriol Vinyals and Lex Friedman: https://youtu.be/Kedt2or9xlo?t=1769, at 29:29, Oriol Vinyals refers to a paper: If you look at research in computer vision where it makes a ...
4
votes
1answer
71 views

Are most things generally discovered because they work empirically and later justified mathematically, or vice-versa?

In the original GloVe paper, the authors discuss group theory when coming up with equation (4). Is it possible that the authors came up with this model, figured out it was good, and then later found ...
4
votes
1answer
67 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. ...
3
votes
4answers
173 views

How can I read any AI paper?

I have studied linear algebra, probability, and calculus twice. But I don't understand how can I reach the level that I can read any AI paper and understand mathematical notation in it. What is your ...
3
votes
2answers
1k views

What should I do when the potential value of a state is too high?

I'm working on a Reinforcement Learning task where I use reward shaping as proposed in the paper Policy invariance under reward transformations: Theory and application to reward shaping (1999) by ...
3
votes
1answer
65 views

What is a non-starving policy in reinforcement learning?

In the paper, Eligibility Traces for off-Policy Policy Evaluation (2010), by Doina Precup et al., mentioned the term "non-starving" many times. The specific use of the term was like "non-starving ...
3
votes
1answer
83 views

How does publishing in the deep learning world work, with respect to journals and arXiv?

Let's say I implemented a new deep learning model that pushed some SOTA a little bit further, and I wrote a new paper about for publication. How does it work now? I pictured three options: Submit it ...
3
votes
1answer
46 views

Do all expert trajectories have the same starting state in apprenticeship learning?

In the apprenticeship learning algorithm described by Ng et al. in Apprenticeship Learning via Inverse Reinforcement Learning, they mention that expert trajectories come in the form of $\{s_0^i, s_1^i\...
3
votes
2answers
69 views

Why is the max a non-expansive operator?

In certain reinforcement learning (RL) proofs, the operators involved are assumed to be non-expansive. For example, on page 6 of the paper Generalized Markov Decision Processes: Dynamic-programming ...
3
votes
1answer
131 views

How is equation 8 derived in the paper “Self-critical sequence training for image captioning”?

In the paper "Self-critical sequence training for image captioning", on page 3, they define the loss function (of the parameters $\theta$) of an image captioning system as the negative expected reward ...
3
votes
2answers
809 views

What is a bad local minimum in machine learning?

What is "bad local minima"? The following papers all mention this expression. Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit limination of All Bad Local ...
3
votes
1answer
72 views

Is unsupervised disentanglement really impossible?

In Locatello et al's Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations he claims to prove unsupervised disentanglement is impossible. His entire claim is ...
3
votes
0answers
139 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
votes
0answers
38 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
votes
1answer
82 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
votes
1answer
64 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
votes
1answer
336 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 ...
2
votes
1answer
121 views

Can you help me understand how weight normalization works?

I am trying to dissect the paper Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks. Unfortunately, because my math is a little bit rusty, I got a little ...
2
votes
2answers
145 views

Why do we need 10 bits to represent the 1000 classes in AlexNet?

I'm reading the AlexNet paper. In section 4, where the authors explain how they prevent overfitting, they mention Although the 1000 classes of ILSVRC make each training example impose 10 bits of ...
2
votes
1answer
49 views

What is the surrogate loss function in imitation learning, and how is it different from the true cost?

I've been reading A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning lately, and I can't understand what they mean by the surrogate loss function. Some relevant ...
2
votes
1answer
40 views

What is convergence analysis, and why is it needed in reinforcement learning?

While reading a paper about Q-learning in network energy consumption, I came across the section on convergence analysis. Does anyone know what convergence analysis is, and why is convergence analysis ...
2
votes
1answer
52 views

Why should the baseline's prediction be near zero, according to the Integrated Gradients paper?

I am trying to understand Intagrated Gradients, but have difficulty in understanding the authors' claim (in section 3, page 3): For most deep networks, it is possible to choose a baseline such that ...
2
votes
1answer
41 views

Understanding the node information score in the paper “Hierarchical Graph Pooling with Structure Learning”

The paper Hierarchical Graph Pooling with Structure Learning (2019) introduces a distance measure between: a graph's node-representation matrix $\text{H}$, and an approximation of this constructed ...
2
votes
2answers
70 views

How can Siamese Networks be viewed as RNNs?

"Single-object tracking commonly uses Siamese networks, which can be seen as an RNN unrolled over two time-steps." (from the SQAIR paper) I'm wondering how Siamese networks can be viewed as RNNs, as ...
2
votes
2answers
53 views

Is it feasible to use GAN for high-quality image synthesis other than human faces?

The famous Nvidia paper Progressive Growing of GANs for Improved Quality, Stability, and Variation, the GAN can generate hyperrealistic human faces. But, in the very same paper, images of other ...
2
votes
1answer
71 views

Why do we use $D(x \mid y)$ and not $D(x,y)$ in conditional generative adversarial networks?

In conditional generative adversarial networks (GAN), the objective function (of a two-player minimax game) would be $$\min _{G} \max _{D} V(D, G)=\mathbb{E}_{\boldsymbol{x} \sim p_{\text {data }}(\...
2
votes
1answer
51 views

Which work originally introduced gradient clipping?

The Deep Learning book mentions that it's been used for years but the oldest sources it mentions are from 2012: A simple type of solution has been in use by practitioners for many years: clipping ...
2
votes
1answer
85 views

How GoogleNet actually deal with reducing overfitting?

Today I was going through a tutorial of Andrew Ng about Inception network. He said that GoogLeNet's hidden layers are also good in prediction and it had somehow a regularization effect, so it reduces ...
2
votes
0answers
83 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
votes
0answers
47 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
votes
0answers
50 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
votes
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
votes
0answers
34 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
votes
0answers
47 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
votes
0answers
38 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
votes
0answers
46 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
votes
0answers
37 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
votes
0answers
43 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....