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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21
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 ...
20
votes
2answers
9k views

What is sample efficiency, and how can importance sampling be used to achieve it?

For instance, the title of this paper reads: "Sample Efficient Actor-Critic with Experience Replay". What is sample efficiency, and how can importance sampling be used to achieve it?
13
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3answers
8k views

Where can I find the original paper that introduced RNNs?

I was able to find the original paper on LSTM, but I was not able to find the paper that introduced "vanilla" RNNs. Where can I find it?
12
votes
1answer
2k views

How would DeepMind's new differentiable neural computer scale?

DeepMind just published a paper about a differentiable neural computer, which basically combines a neural network with a memory. The idea is to teach the neural network to create and recall useful ...
8
votes
1answer
2k views

What is the difference between logic-based and rule-based AI?

I always thought rule-based was synonymous with logic-based AI. Logic has axioms and rules of inference, whereas rule-based AI has a knowledge base (essentially, axioms) and if-then rules to create ...
7
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2answers
754 views

Where to publish a first article in Deep Reinforcement Learning?

What would be examples of journals that are good for a first publication in the field of Deep Reinforcement Learning? I am in the process of writing about the research results of DQN-related ...
6
votes
2answers
253 views

Why are reinforcement learning methods sample inefficient?

Reinforcement learning methods are considered to be extremely sample inefficient. For example, in a recent DeepMind paper by Hessel et al., they showed that in order to reach human-level performance ...
6
votes
1answer
339 views

How to express a fully connected neural network succintly using linear algebra?

I'm currently reading the paper Federated Learning with Matched Averaging (2020), where the authors claim: A basic fully connected (FC) NN can be formulated as: $\hat{y} = \sigma(xW_1)W_2$ [...] ...
6
votes
2answers
74 views

What does “semantic gap” mean?

I was reading DT-LET: Deep transfer learning by exploring where to transfer, and it contains the following: It should be noted direct use of labeled source domain data on a new scene of target domain ...
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 ...
6
votes
1answer
2k 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 ...
6
votes
1answer
129 views

Why can't I reproduce the experiments in the original paper that introduced the Firefly Algorithm?

I have been trying to reproduce the experiments done in the original: Firefly Algorithm for multimodal optimization (2010) by Xin-She Yang, but so far unsuccessfully. For the moment being, I'm okay if ...
6
votes
1answer
79 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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1answer
554 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
1answer
889 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
87 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: ...
5
votes
1answer
139 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
623 views

In YOLO, when is $\mathbb{1}_{i j}^{\mathrm{obj}} = 1$, and what are the ground-truth labels for $x_i$ and $y_i$?

I'm trying to implement a custom version of the YOLO neural network. Originally, it was described in the paper You Only Look Once: Unified, Real-Time Object Detection (2016). I have some problems ...
5
votes
0answers
73 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 ...
4
votes
2answers
111 views

Why do we use $X_{I_t,t}$ and $v_{I_t}$ to denote the reward received and the at time step $t$ and the distribution of the chosen arm $I_t$?

I'm doing some introductory research on classical (stochastic) MABs. However, I'm a little confused about the common notation (e.g. in the popular paper of Auer (2002) or Bubeck and Cesa-Bianchi (2012)...
4
votes
1answer
638 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
913 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
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1answer
70 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
299 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
63 views

What is the relation between self-taught learning and transfer learning?

I am new to transfer learning and I start by reading A Survey on Transfer Learning, and it stated the following: according to different situations of labeled and unlabeled data in the source domain, ...
4
votes
1answer
80 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
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0answers
41 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
91 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: ...
3
votes
4answers
201 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
1answer
587 views

What are some resources on computational learning theory?

Pretty soon I will be finishing up Understanding Machine Learning: From Theory to Algorithms by Shai Ben-David and Shai Shalev-Shwartz. I absolutely love the subject and want to learn more, the only ...
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
2answers
58 views

Why some neural network models in the 1980s shown as circuit models

I am familiar with the currently popular neural network models that have weights and are trained with backpropagation and gradient descent. However, I came across a different type of neural network ...
3
votes
2answers
237 views

What are some books or state of the art papers about the development of a strong-AI?

I am looking for books or to state of the art papers about current the development trends for a strong-AI. Please, do not include opinions about the books, just refer the book with a brief ...
3
votes
1answer
98 views

Which books or papers clearly explain the relation between Ising models and deep neural networks?

I am looking for a book or paper which clearly explains the relationship between Ising models and deep neural networks. Can anyone provide any references?
3
votes
1answer
80 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
220 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
49 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
83 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
2answers
68 views

What does the parameter $y$ stand for in function $g(y,\mu,\sigma)$ related to REINFORCE algorithm?

I am wondering what the parameter $y$ in the function $g(y,\mu,\sigma)=\frac{1}{(2\pi)^{1/2}\sigma}e^{-(y-\mu)^{2/2\sigma^2}}$ stands for in Section 6 (page 14) of the paper introducing the REINFORCE ...
3
votes
2answers
105 views

What is different in each head of a multi-head attention mechanism?

I have a difficult time understanding the "multi-head" notion in the original transformer paper. What makes the learning in each head unique? Why doesn't the neural network learn the same ...
3
votes
1answer
71 views

How is MuZero's second binary plane for chess defined?

From the MuZero paper (Appendix E, page 13): In chess, 8 planes are used to encode the action. The first one-hot plane encodes which position the piece was moved from. The next two planes encode ...
3
votes
1answer
151 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
1k 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
88 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
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
52 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
votes
0answers
150 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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0answers
103 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
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
votes
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 ...

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