Questions tagged [reference-request]

Use when requesting examples of research or research papers, books, articles, blog posts or courses. For example, "Is there any published research about X?" or "What are good examples of Y in research?".

149 questions with no upvoted or accepted answers
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171 views

What are the state-of-the-art results in OpenAI's gym environments?

What are the state-of-the-art results in OpenAI's gym environments? Is there a link to a paper/article that describes them and how these SOTA results were calculated?
6
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0answers
65 views

Are there transformer-based architectures that can produce fixed-length vector encodings given arbitrary-length text documents?

BERT encodes a piece of text such that each token (usually words) in the input text map to a vector in the encoding of the text. However, this makes the length of the encoding vary as a function of ...
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0answers
71 views

Why are most commonly used activation functions continuous?

I have come to notice that the most commonly used activation functions are continuous. Is there any specific reason behind this? Results such as this paper have worked on training networks with ...
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2answers
90 views

How do you measure multi-label classification accuracy?

Multi-label assignment is the task in machine learning to assign to each input value a set of categories from a fixed vocabulary where the categories need not be statistically independent, so ...
4
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0answers
84 views

Forcing a neural network to be close to a previous model - Regularization through given model

I'm wondering, has anyone seen any paper where one trains a network but biases it to produce similar outputs to a given model (such as one given from expert opinion or it being a previously trained ...
4
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0answers
183 views

Is there a way to do reinforcement learning in POMDP?

Are there any algorithms to use reinforcement learning to learn optimal policies in partially observable Markov decision process (POMDP) i.e. when the state is not perfectly observed? More ...
4
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0answers
40 views

What are some neural network models that can use auxiliary info during training for image segmentation?

What are some deep learning models that can use supplementary information other than RGB channels for image segmentation? For example, imagine a poorly shot image of a river (blue) that shows a gap, ...
4
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0answers
53 views

What research has been done on learning non-Markovian reward functions?

Recently, some work has been done planning and learning in Non-Markovian Decision Processes, that is, decision-making with temporally extended rewards. In these settings, a particular reward is ...
4
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0answers
639 views

Is there any way and any reason why one would introduce a sparsity constraint on a deep auto-encoder?

Is there any way and any reason why one would introduce a sparsity constraint on a deep autoencoder? In particular, in deep autoencoders, the first layer often has more units than the dimensionality ...
3
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1answer
86 views

What algorithms are used in Artificial General Intelligence research?

I've read on wiki that already in 2017 there were over 40 institutions researching AGI, and I wonder what type of algorithms are being studied and developed in this field. For example, for comparison ...
3
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1answer
99 views

Current research on Gödel machines

Is there any current research on Gödel machines? It seems that the last article by Jürgen Schmidhuber on this topic was published in 2012: http://people.idsia.ch/~juergen/goedelmachine.html
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95 views

How can I generate artificial conversations between two AIs?

I am building an artificial town that has randomly generated people with different personalities. People in this artificial town have attributes that change their happiness, ego, rep, etc. I already ...
3
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0answers
49 views

How efficient is SCAWI weight initialization method?

I'm currently in the middle of a project (for my thesis) constructing a deep neural network. Since I'm still in the research part, I'm trying to find various ways and techniques to initialize weights. ...
3
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1answer
101 views

Which machine learning method can take a matrix as input?

I am pretty new to the machine learning field. I want to use an $n \times m$ matrix as the input of a model, in order to predict a vector $1 \times m$, both of real numbers. Input data are quite clean,...
3
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0answers
80 views

Is there a good book or paper on word embeddings?

Is there a good and modern book that focuses on word embeddings and their applications? It would also be ok to provide the name of a paper that provides a good overview of word embeddings.
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0answers
78 views

What are examples of good reference books on unsupervised learning?

I am looking for good introductory and advanced books on unsupervised learning. I have already read books like Probabilistic Graphical Models from D. Kholler and Pattern Recognition and Machine ...
3
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1answer
548 views

Is Christopher Bishop's "Pattern Recognition and Machine Learning" out of date in 2018?

I recently came across a reference to a book that was highly regarded: "Pattern Recognition and Machine Learning" by Christopher Bishop. I am a beginner working my way through some machine ...
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0answers
879 views

Can neural networks be used to study (elementary) number theoretic problems?

Can neural networks be used to study (elementary) number theoretic problems? What are examples where this has been done in the past? Or is there on the contrary an understanding that neural networks ...
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45 views

Why does TD (0) converge to the MLE solution of the Markov model?

Why does TD (0) converge to the MLE solution of the Markov model? Let's take the Example 6.4 in Sutton and Barto's book as an example. Example 6.4: You are the Predictor Place yourself now in the ...
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34 views

Did the unsolved XOR problem in "Perceptrons: An Introduction to Computational Geometry" 1969 book really cause the winter of the AI in 1974?

Winter of AI definition: periods of reduced funding and interest in artificial intelligence research, due to unmet expectations after a period of hype. There have been at least two major AI winters ...
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0answers
36 views

Has the idea of using different learning rates for different layers been explored in the literature?

I wonder whether there are heuristic rules for the optimal selection of learning rates for different layers. I expect that there is no general recipe, but probably there are some choices that may be ...
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0answers
41 views

How much research, approximately, is done in ANNs?

Does someone know where can I find information about how much research, nowadays, is done in ANNs? I've checked in this document Redes Neuronales: Conceptos básicos y aplicaciones, Universidad ...
2
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1answer
80 views

How could Bayesian neural networks be used for transfer learning?

In transfer learning, we use big data from similar tasks to learn the parameters of a neural network, and then fine-tune the neural network on our own task that has little data available for it. Here, ...
2
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0answers
82 views

Are there heuristics that play Klondike Solitaire well?

Are there heuristics that play Klondike Solitaire well? I know there are some good exhaustive search solvers for Klondike Solitaire. The best one that I know of is Solvitaire (2019) which uses DFS, (...
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0answers
58 views

What is the effect of K in K-NN on the VC dimension?

What is the effect of K in K-NN on the VC dimension? When K increases, is the VC dimension decreased or increased, or we can't say anything about this? Is there a reference book that discusses this?
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38 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 ...
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0answers
43 views

What is the first short film completely made by AI?

I have created (not me exactly) a short film entirely made by AI. There many short films (like Sunspring) 'written' by AI but were acted out by humans. In my short film, the story is by the AI, the ...
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0answers
25 views

What are some of the main high level approaches to applying ML on kinematic sensor data?

I've just started a project which will involve having to detect certain events in a stream of kinematic sensor data. By searching through the literature, I've found a lot of highly specific papers, ...
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0answers
65 views

Are there any new weight initialization techniques for DNN published after 2015?

Considering weights initialization in my personal projects, I always used some standard techniques such as: Glorot (also known as Xavier) initialization (2010). Mertens initialization (2010). He ...
2
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0answers
20 views

Can DQN outperform DoubleDQN?

I found a similar post about this issue, but unfortunately I did not find a proper answer. Are there any references where DQN is better than DoubleDQN, that is DoubleDQN does not improve DQN ?
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31 views

Literature on the advantages of using an auto-encoder for classification

Given a supervised problem with X, y input pairs, one can do two things for obtaining the function f that maps X with y with Neural Networks (and in general in machine learning): Deploy directly a ...
2
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0answers
55 views

Combine DQN with the Average Reward setting

I have to deal with a non-episodic task, where there is addittionally a continuous state space and more specifically in each time step there is always a new state that has never been seen before. I ...
2
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0answers
48 views

What is the proof that the variance of the gradient estimate in Actor-Critic is smaller than in REINFORCE?

The intuition provided when introducing actor-critic algorithms is that the variance of its gradient estimates is smaller than in REINFORCE as, e.g., discussed here. This intuition makes sense for the ...
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0answers
39 views

What are the applications of hierarchical softmax?

Apart from its use in word embeddings (e.g word2vec algorithm), are there any other applications of hierarchical softmax? If yes, can you please give me some reference papers?
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0answers
27 views

Is there any published research on the information-carrying capacity of the human face?

Is there any published research on the information-carrying capacity of the human face? Here I mean "how much information can be conveyed via facial expressions & micro-expressions". This is a ...
2
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0answers
34 views

Is there an online RL algorithm that receives as input a camera frame and produces an action as output?

I want to build a reinforcement learning model, which takes a camera picture as input, that learns online (in terms of machine learning). Based on the position of an object on the camera, I want the ...
2
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0answers
46 views

When to do discretization to decrease the state/action space in RL?

When to do discretization to decrease the state/action space in RL? Can you give me some references that such a technique is used?
2
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0answers
137 views

What is the original source of the TD Advantage Actor-Critic algorithm?

What is the original source of the TD Advantage Actor-Critic algorithm? I found this tutorial really helpful for learning the algorithm. However, what is the original source of this algorithm?
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0answers
37 views

Is there a theory that captures the following ideas?

A big class of problems that are relevant in today's society are full of uncertainty and are also sometimes computationally intractable. Along our lives we come to realize that we are solving the same ...
2
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1answer
2k views

What are some good alternatives to U-Net for biomedical image segmentation?

Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). Is there a neural network, that can compete with U-Net, in ...
2
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0answers
29 views

Will structured knowledge bases continue to be used in question answering with the likes of BERT gaining popularity?

This may come across as an open and opinion-based question, I definitely want to hear expert opinions on the subject, but I am also looking for references to materials that I can read deeply. One of ...
2
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0answers
22 views

Is there an up-to-date list of suitable kernels for Gaussian processes?

Consider a stochastic process $\{X_t \colon t \in T\}$ indexed by a set $T$. We assume for simplicty that $T \in \mathbb{R}^n$. We assume that for any choice of indexes $t_1, \dots, t_n$, the random ...
2
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0answers
43 views

What is currently the most competitive regression models/algorithms used on the "Boston Housing Prices" dataset?

I'm currently looking for a standard data-set to test some new regression models I've been developing on, and the "Boston Housing Prices" data-set seemed to stand out, since it's very ...
2
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0answers
28 views

Did people analyze dynamics of very simple LSTMs?

I wonder if researchers tried to understand how LSTMs work by analyzing the dynamics of simple LSTM (e.g. with 2 units)? For example, how the hidden state evolves depending on the properties of weight ...
2
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0answers
35 views

References on generalization theory and mathematical abstraction of ML concepts

I'd like to learn about generalization theory for machine learning algorithms. I'm looking for books and other references (in case books aren't available) that provide a gentle introduction to the ...
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0answers
382 views

Is it possible to create a decompiler using AI?

I would like to decompile a compiled file to source code. Is it possible to use any AI technique to perform decompilation? Is there any research on this topic? If yes, can you briefly explain one of ...
2
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0answers
30 views

Is there a detailed description or implementation of an end-to-end speech recognition system?

I am currently trying to implement an end-to-end speech recognition system from scratch, that is, without using any of the existing frameworks (like TensorFlow, Keras, etc.). I am building my own ...
2
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0answers
687 views

Can we combine multiple different neural networks in one?

I want to make a kind of robotic brain, i.e. a big neural network, which includes an NLP model (for understanding human voice), real-time object recognition system (so that it can identify particular ...
2
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3answers
190 views

Is there a neural network in the literature that predicts the next game state based on the current state and the action?

I am trying to find literature on a network architecture that takes the following as in input: Action (like 'Up', 'Down', etc) Image of the current state and outputs: Image of next state I already ...
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0answers
17 views

Is there a paper/article on contextual $\epsilon$-greedy algorithm?

I am reading the paper A Contextual-Bandit Approach to Personalized News Article Recommendation, where it refers to $\epsilon$-greedy (disjoint) algorithm. I suspect, that it is just a version of a K-...