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- This is a summary of the paper titled: "Learning to Teach", authored by Yang Fan, Fei Tian, Tao Qin, Xiang-Yang Li, and Tie-Yan ...ent, determining the appropriate data, loss function, and hypothesis space to facilitate the learning of the student model. ...21 KB (3,351 words) - 18:40, 16 December 2018
- 54 bytes (12 words) - 09:46, 30 August 2017
- ...label or a non-localized caption. The authors of 'Learning What and Where to Draw' believe that image synthesis will be drastically enhanced by incorpor ...scription what each image is intended to depict. The proposed model learns to perform location and content-controllable image synthesis on the Caltech-UC ...18 KB (2,781 words) - 12:35, 4 December 2017
- </ref>. Now we turn to ...204 bytes (22 words) - 09:45, 30 August 2017
- ...er are able to generate samples that are comparable or better when applied to domains of images and structured objects. The authors point to several drawbacks currently associated with VAE's including: ...15 KB (2,313 words) - 19:11, 2 December 2020
- #REDIRECT [[link to my paper]] ...30 bytes (5 words) - 09:45, 30 August 2017
- #REDIRECT [[sandbox to test w2l]] ...33 bytes (6 words) - 09:46, 30 August 2017
- ...ons between them. An explicit representation of this semantics is referred to as a scene graph where we represent objects grounded in the scene as vertic ...all of the objects in the scene, then isolate individual pairs of objects to identify the relationships between them. This breakdown often restricts the ...17 KB (2,749 words) - 18:26, 16 December 2018
- This is a summary of the paper "Towards Deep Learning Models Resistant to Adversarial Attacks" by Aleksander Madry, Aleksandar Makelov, Ludwig Schmid ...e|'''Figure 1.''' Before and after an input image of a panda was subjected to perturbations.<sup>[https://arxiv.org/abs/1412.6572 Source]</sup>]] ...14 KB (2,192 words) - 03:01, 23 November 2018
- #REDIRECT [[learning Spectral Clustering, With Application To Speech Separation]] ...81 bytes (9 words) - 09:45, 30 August 2017
- [https://arxiv.org/pdf/1804.00168.pdf Learning to Navigate in Cities Without a Map] ...forcement learning (RL), it suffers from data inefficiency and sensitivity to changes in the environment. Thus, it is unclear whether this method could b ...28 KB (4,494 words) - 00:24, 17 December 2018
- ...hat generalizes to the unseen datasets when spectral clustering is applied to them. Traditional spectral clustering techniques assume a metric or a simil Clustering refers to partition a given dataset into clusters such that data points in the same c ...35 KB (5,767 words) - 09:45, 30 August 2017
- ...ue function, directly on latent state samples which help to enable scaling to more complex tasks. ...omes with using finite imagination horizons. The authors have also managed to demonstrate empirical performance for visual control by evaluating the mode ...13 KB (2,072 words) - 06:07, 10 December 2020
- ...hod is more effective compared to other neural network models when applied to long sentences. ...word. The decoder then selectively combines the most relevant annotations to generate each target word; this implements a mechanism of attention in the ...14 KB (2,221 words) - 09:46, 30 August 2017
- ...for analyzing individual predictions made by the LSTMs without any change to the underlying original model. The problem of sentiment analysis is chosen ...n domain, this paper shows how the contextual decomposition method is used to successfully extract positive and negative negations from an LSTM. This pap ...31 KB (5,069 words) - 18:21, 16 December 2018
- #REDIRECT [[rOBPCA: A New Approach to Robust Principal Component Analysis]] ...75 bytes (10 words) - 09:46, 30 August 2017
- ...proposes that the subnetworks can achieve similar accuracy without having to be further trained. However, finding these lottery tickets inside a large n ...theoretical guarantees of pruning. This study, ''A Probabilistic Approach to Neural Network Pruning'' by Xin Qian and Diego Klabjan [18], focuses on the ...28 KB (4,367 words) - 00:30, 23 November 2021
- ...alternative conclusions. Each class consists of three players who compete to find evidence for both factual and counterfactual circumstances. In a simpl ...ng explanations for a specific class by probing the importance with regard to the relevant class logit. ...11 KB (1,594 words) - 13:14, 25 November 2021
- #REDIRECT [[neural Machine Translation: Jointly Learning to Align and Translate]] ...81 bytes (10 words) - 09:46, 30 August 2017
- ...ix. Since the classical estimation for covariance matrix is very sensitive to the presence of outliers, it is not surprising that the principal component ...to show that Bayesian robust estimator may be alternative choice compared to classical robust estimators. ...15 KB (2,414 words) - 09:46, 30 August 2017
Page text matches
- ...experience, yet in complex domains for which a simulator is not available to the agents, the performance of model-based agents employing standard planni ...ct useful knowledge gathered from model simulations. This allows the agent to benefit from model-based imagination without the pitfalls of conventional m ...2 KB (210 words) - 20:39, 9 March 2018
- ...ed using a convex combination to a number of clusters rather than uniquely to one cluster. This is an unsupervised version of the so-called multi-class c ...e data, authors have recently proposed discrete analogues to PCA. We refer to the method as multinomial PCA(mPCA) because it is a precise multinomial ana ...2 KB (321 words) - 09:45, 30 August 2017
- ...ean discrepancy (JMMD) criterion. Adversarial training strategy is adopted to maximize JMMD such that the distributions of the source and target domains ...760 bytes (109 words) - 15:32, 2 October 2017
- #REDIRECT [[link to my paper]] ...30 bytes (5 words) - 09:45, 30 August 2017
- #REDIRECT [[sandbox to test w2l]] ...33 bytes (6 words) - 09:46, 30 August 2017
- ...lt but there exists a probability distribution function g(x) which is easy to sample from, then <math>I</math> can be written as<br> ...playstyle E_g(w(x)) \rightarrow</math>the expectation of w(x) with respect to g(x) ...2 KB (395 words) - 09:45, 30 August 2017
- #REDIRECT [[learning Spectral Clustering, With Application To Speech Separation]] ...81 bytes (9 words) - 09:45, 30 August 2017
- #REDIRECT [[neural Machine Translation: Jointly Learning to Align and Translate]] ...81 bytes (10 words) - 09:46, 30 August 2017
- #REDIRECT [[rOBPCA: A New Approach to Robust Principal Component Analysis]] ...75 bytes (10 words) - 09:46, 30 August 2017
- #REDIRECT [[a Rank Minimization Heuristic with Application to Minimum Order System Approximation]] ...98 bytes (12 words) - 09:45, 30 August 2017
- #REDIRECT [[a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization]] ...105 bytes (12 words) - 09:45, 30 August 2017
- To properly train a neural network a large labeled dataset, however large data These models scale linearly in proportion to the number of classes in the data sets. The number of evaluations could be ...466 bytes (70 words) - 09:46, 30 August 2017
- #REDIRECT [[a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis]] ...131 bytes (15 words) - 09:45, 30 August 2017
- ...the methods used for video-based face recognition were based on the still-to-still techniques which aimed at selecting good frame and then performed som ...s kind of application, which is called online video. The other scenario is to process the video content offline, like indexing the meeting records or ana ...3 KB (512 words) - 09:45, 30 August 2017
- ...ifically, this paper explores whether we can train machine learning models to learn from dialog. *Evaluated some baseline models on this data and compared them to standard supervised learning. ...2 KB (309 words) - 19:52, 17 November 2020
- ...RECT [[graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns]] ...145 bytes (17 words) - 09:46, 30 August 2017
- #REDIRECT [[stat946f15/Sequence to sequence learning with neural networks]] ...75 bytes (10 words) - 09:46, 30 August 2017
- #REDIRECT [[from Machine Learning to Machine Reasoning]] ...56 bytes (7 words) - 09:46, 30 August 2017
- ...following table. Put your name and a link to the paper that you are going to present. Chose a date between Nov 16 and Dec 2 (inclusive). .../Correlate/pmd.pdf], [[A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis|Summary]] ...4 KB (570 words) - 09:45, 30 August 2017
- ...a document they will not examine the next document. This model is similar to hidden Markov model in that there is a conditional dependency between the p ...that if a URL clicked by a user that means it’s both examined and relevant to the query . In another word , given a query q , position i and URL u the pr ...3 KB (593 words) - 09:46, 30 August 2017