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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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13 views

How is the general return-based off-policy equation derived?

I'm wondering how is the general return-based off-policy equation in Safe and efficient off-policy reinforcement learning derived $$\mathcal{R} Q(x, a):=Q(x, a)+\mathbb{E}_{\mu}\left[\sum_{t \geq 0} \...
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1answer
52 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
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1answer
54 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. ...
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0answers
20 views

Why do both sine and cosine have been used in positional encoding in the transformer model?

The Transformer model proposed in "Attention Is All You Need" uses sinusoid functions to do the positional encoding. Why have both sine and cosine been used? And why do we need to separate the odd ...
3
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1answer
57 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 ...
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0answers
22 views

Reference request: one-hot encoding outperforming random orthogonal encoding

I experimented with a CNN operating on texts encoded as sequences of character vectors, where characters are encoded as one-hot vectors in one embedding and as random unit length pairwise orthogonal ...
2
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0answers
22 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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1answer
43 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 ...
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1answer
66 views

What is an identity recurrent neural network?

What is an identity recurrent neural network (IRNN)? What is the difference between an IRNN and RNN?
2
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1answer
35 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 ...
4
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1answer
102 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') ...
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13 views

Derivation for Value Iteration of CVaR

I am reading a paper named Risk-sensitive and Robust Decision-making: a CVaR Optimization Approach. In appendix A.3 they provide a proof for their Theorem $4$. The $n=1$ case for equation (11) is ...
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1answer
43 views

Understanding the reconstruction loss in the paper “Anomaly Detection using Deep Learning based Image Completion”

I would like to implement the approach represented in this paper. Here they used following reconstruction loss: $$ L(X)= \frac{\lambda \cdot || M \odot (X - F(\overline{M} \odot X)) ||_{1} + (1 - \...
2
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1answer
45 views

What is “dense” in DensePose?

I've recently come across an amazing work for human pose estimation: DensePose: Dense Human Pose Estimation In The Wild by Facebook. In this work, they have tackled the task of dense human pose ...
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0answers
69 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 ...
4
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1answer
108 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 ...
4
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1answer
70 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 ...
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1answer
29 views

Understanding how the loss was calculated for the SQuAD task in BERT paper

In the BERT paper, section 4.2 covers the SQuAD training. From my understanding, there are two extra parameters trained, they are two vectors with the same dimension as the hidden size, so the same ...
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1answer
40 views

IQN bellman target: using Z vs using Q

IQN paper (https://arxiv.org/abs/1806.06923) uses distributional bellman target: $$ \delta^{\tau,\tau'}_t = r_t + \gamma Z_{\tau'}(x_{t+1}, \pi_{\beta}(x_{t+1})) - Z_{\tau}(x_t, a_t) $$ And optimizes: ...
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2answers
55 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 ...
2
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0answers
80 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 ...
2
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1answer
31 views

How could we estimate the square footage of a room from an image?

I wonder if it would be possible to know the size of a room using image, I don't see anything about this subject, do you have some idea how it could be done?
3
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1answer
85 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 ...
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2answers
407 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 ...
5
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1answer
2k 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?
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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 ...
4
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1answer
474 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
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1answer
227 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 ...
1
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1answer
71 views

How is the word embedding represented in the paper “Recurrent neural network based language model”?

I'm reading "Recurrent neural network based language model" of Mikolov et al. (2010). Although the article is straight forward, I'm not sure how word embedding $w(t)$ is obtained: The reason I wonder ...