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Ensemble Estimation of Information Divergence
Ensemble Estimation of Information Divergence
Information Theory
 
Gradient Descent for Spiking Neural Networks
Gradient Descent for Spiking Neural Networks
Deep Learning
 
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Causal Inference
 
Action Centered Contextual Bandits
Action Centered Contextual Bandits
Deep Learning
 
BlockDrop: Dynamic Inference Paths in Residual Networks
BlockDrop: Dynamic Inference Paths in Residual Networks
Computer Vision
 
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
RobustnessNatural Language Processing
 
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Efficient AIDeep Learning
 
Learning to Separate Object Sounds by Watching Unlabeled Video
Learning to Separate Object Sounds by Watching Unlabeled Video
Computer Vision
 
The Sound of Pixels
The Sound of Pixels
Multimodal LearningComputer Vision
 
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Multi-agent SystemsReinforcement Learning
 
Dialog-based Interactive Image Retrieval
Dialog-based Interactive Image Retrieval
Computer Vision
 
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Computer VisionGenerative Models
 
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
OptimizationDeep Learning
 
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
RobustnessOptimization
 
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Computer VisionFew-shot Learning
 
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
RobustnessExplainability
 
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Generative Models
 
Deriving Machine Attention from Human Rationales
Deriving Machine Attention from Human Rationales
Deep RationalizationNatural Language Processing
 
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
AI in HealthcareNatural Language Processing
 
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Generative ModelsGraph Deep Learning
 
Learning Entropic Wasserstein Embeddings
Learning Entropic Wasserstein Embeddings
Machine LearningOptimal Transport
 
signSGD via Zeroth-Order Oracle
signSGD via Zeroth-Order Oracle
OptimizationRobustness
 
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Neuro-Symbolic AIComputer Vision
 
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
AI in HealthcareDeep Learning
 
Experimental Design for Cost-Aware Learning of Causal Graphs
Experimental Design for Cost-Aware Learning of Causal Graphs
Causal Inference
 
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
Computer VisionTime Series
 
Co-regularized Alignment for Unsupervised Domain Adaptation
Co-regularized Alignment for Unsupervised Domain Adaptation
Transfer LearningDeep Learning
 
Unsupervised learning with contrastive latent variable models
Unsupervised learning with contrastive latent variable models
Unsupervised Learning
 
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
Multi-agent Systems
 
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
Generative ModelsExplainability
 
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Robustness
 
Scalable Graph Learning for Anti-Money Laundering: A First Look
Scalable Graph Learning for Anti-Money Laundering: A First Look
AI in FinanceGraph Deep Learning
 
Neural Network Robustness Certification with General Activation Functions
Neural Network Robustness Certification with General Activation Functions
RobustnessDeep Learning
 
Weakly Supervised Dense Event Captioning in Videos
Weakly Supervised Dense Event Captioning in Videos
Computer Vision
 
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Robustness
 
Tight Certificates of Adversarial Robustness
Tight Certificates of Adversarial Robustness
CybersecurityNeurIPS
 
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
Natural Language Processing
 
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
Computer Vision
 
Unsupervised learning by competing hidden units
Unsupervised learning by competing hidden units
PNASUnsupervised Learning
 
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Neuro-Symbolic AIComputer Vision
 
Bayesian Nonparametric Federated Learning of Neural Networks
Bayesian Nonparametric Federated Learning of Neural Networks
Federated Learning
 
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Graph Deep LearningNatural Language Processing
 
Variational Russian Roulette for Deep Bayesian Nonparametrics
Variational Russian Roulette for Deep Bayesian Nonparametrics
Deep LearningBayesian Modeling
 
Write, Execute, Assess: Program Synthesis with a REPL
Write, Execute, Assess: Program Synthesis with a REPL
Program Synthesis
 
Deep Leakage from Gradients
Deep Leakage from Gradients
RobustnessDeep Learning
 
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Computer VisionTime Series
 
Neural language models as psycholinguistic subjects: Representations of syntactic state
Neural language models as psycholinguistic subjects: Representations of syntactic state
Natural Language ProcessingTime Series
 
Local Unsupervised Learning for Image Analysis
Local Unsupervised Learning for Image Analysis
Unsupervised LearningComputer Vision
 
Defensive Quantization: When Efficiency Meets Robustness
Defensive Quantization: When Efficiency Meets Robustness
Efficient AIRobustness
 
Watch, Reason and Code: Learning to Represent Videos Using Program
Watch, Reason and Code: Learning to Represent Videos Using Program
Computer Vision
 
Seeing What a GAN Cannot Generate
Seeing What a GAN Cannot Generate
Generative Models
 
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Lifelong LearningTransfer Learning
 
The Future of Work: How New Technologies Are Transforming Tasks
The Future of Work: How New Technologies Are Transforming Tasks
Future of Work
 
Cross-channel Communication Networks
Cross-channel Communication Networks
Deep LearningComputer Vision
 
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
Generative ModelsExplainability
 
Reverse-engineering causal graphs with soft interventions
Reverse-engineering causal graphs with soft interventions
Causal Inference
 
New tricks from old dogs: multi-source transfer learning
New tricks from old dogs: multi-source transfer learning
Transfer LearningExplainability
 
Class-wise rationalization: teaching AI to weigh pros and cons
Class-wise rationalization: teaching AI to weigh pros and cons
Natural Language ProcessingDeep Rationalization
 
Causal inference is expensive. Here’s an algorithm for fixing that.
Causal inference is expensive. Here’s an algorithm for fixing that.
Causal Inference
 
Visual Concept-Metaconcept Learning
Visual Concept-Metaconcept Learning
Neuro-Symbolic AI
 
Alleviating label switching with optimal transport
Alleviating label switching with optimal transport
Optimal Transport
 
Topics are more meaningful than words. AI for comparative literature.
Topics are more meaningful than words. AI for comparative literature.
Natural Language ProcessingOptimal Transport
 
Imitation learning from observations
Imitation learning from observations
Deep Learning
 
Using geometry to understand documents
Using geometry to understand documents
Natural Language Processing
 
SPAHM: Parameter matching for model fusion
SPAHM: Parameter matching for model fusion
Bayesian Modeling
 
Big-Little-Video-Net: Work smarter, not harder, for video understanding
Big-Little-Video-Net: Work smarter, not harder, for video understanding
Computer Vision
 
ZO-AdaMM: Derivative-free optimization for black-box problems
ZO-AdaMM: Derivative-free optimization for black-box problems
OptimizationNeurIPS
 
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Deep LearningBayesian Modeling
 
Embedding Compression with Isotropic Iterative Quantization
Embedding Compression with Isotropic Iterative Quantization
Natural Language Processing
 
Automating machine learning with a joint selection framework
Automating machine learning with a joint selection framework
AutoMLEfficient AI
 
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
Graph Deep LearningAAAI
 
A content-aware attack generator for AI cybersecurity
A content-aware attack generator for AI cybersecurity
Adversarial Machine LearningCybersecurity
 
A unifying framework for expectation-aware AI planning
A unifying framework for expectation-aware AI planning
Automated Planning
 
Reading between the lines with graph deep learning for NLP
Reading between the lines with graph deep learning for NLP
Natural Language ProcessingAAAI
 
Online AI planning with graph neural networks and adaptive scheduling
Online AI planning with graph neural networks and adaptive scheduling
Automated PlanningGraph Deep Learning
 
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
Optimization
 
Sentence Embedding Alignment for Lifelong Relation Extraction
Sentence Embedding Alignment for Lifelong Relation Extraction
Natural Language ProcessingLifelong Learning
 
Moments in Time Dataset: one million videos for event understanding
Moments in Time Dataset: one million videos for event understanding
Computer VisionMultimodal Learning
 
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
AI in FinanceGraph Deep Learning
 
Self-supervised Moving Vehicle Tracking with Stereo Sound
Self-supervised Moving Vehicle Tracking with Stereo Sound
Multimodal LearningComputer Vision
 
The sound of motions
The sound of motions
Computer Vision
 
TSM: Temporal Shift Module for Efficient Video Understanding
TSM: Temporal Shift Module for Efficient Video Understanding
Efficient AIComputer Vision
 
Graph Convolutional Networks for Temporal Action Localization
Graph Convolutional Networks for Temporal Action Localization
Graph Deep LearningComputer Vision
 
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
OptimizationRobustness
 
Reasoning about Human-Object Interactions through Dual Attention Networks
Reasoning about Human-Object Interactions through Dual Attention Networks
Computer Vision
 
LaSO: Label-Set Operations networks for multi-label few-shot learning
LaSO: Label-Set Operations networks for multi-label few-shot learning
Computer VisionFew-shot Learning
 
SpotTune: Transfer Learning through Adaptive Fine-tuning
SpotTune: Transfer Learning through Adaptive Fine-tuning
Computer VisionTransfer Learning
 
RepMet: Representative-based metric learning for classification and one-shot object detection
RepMet: Representative-based metric learning for classification and one-shot object detection
Computer Vision
 
ObjectNet: A bias-controlled dataset object recognition
ObjectNet: A bias-controlled dataset object recognition
Computer VisionNeurIPS
 
Point-Voxel CNN for Efficient 3D Deep Learning
Point-Voxel CNN for Efficient 3D Deep Learning
Efficient AIDeep Learning
 
CASTER: An AI framework for preventing adverse reactions to medication
CASTER: An AI framework for preventing adverse reactions to medication
AI in HealthcareAAAI
 
Adversarial Robustness vs Model Compression, or Both?
Adversarial Robustness vs Model Compression, or Both?
Robustness
 
Reshaping Diverse Planning
Reshaping Diverse Planning
Automated Planning
 
Deep Symbolic Superoptimization Without Human Knowledge
Deep Symbolic Superoptimization Without Human Knowledge
Neuro-Symbolic AIOptimization
 
A Closer Look at Deep Policy Gradients
A Closer Look at Deep Policy Gradients
OptimizationICLR
 
Deep Audio Priors Emerge From Harmonic Convolutional Networks
Deep Audio Priors Emerge From Harmonic Convolutional Networks
Audio ProcessingDeep Learning
 
Once for All: Train One Network and Specialize it for Efficient Deployment
Once for All: Train One Network and Specialize it for Efficient Deployment
Efficient AIICLR
 
Implementation Matters in Deep RL: A Case Study on PPO and TRPO
Implementation Matters in Deep RL: A Case Study on PPO and TRPO
Reinforcement LearningOptimization
 
Generative Ratio Matching Networks
Generative Ratio Matching Networks
Generative ModelsDeep Learning
 
Learning Rate Rewinding for elegant neural network pruning
Learning Rate Rewinding for elegant neural network pruning
Efficient AIDeep Learning
 
Layer-wise federated learning with FedMA
Layer-wise federated learning with FedMA
Federated Learning
 
Learning to learn with distributional signatures for text data
Learning to learn with distributional signatures for text data
Natural Language ProcessingTransfer Learning
 
Fast and efficient black-box testing for AI cybersecurity
Fast and efficient black-box testing for AI cybersecurity
CybersecurityRobustness
 
CLEVRER: The first video dataset for neuro-symbolic reasoning
CLEVRER: The first video dataset for neuro-symbolic reasoning
Neuro-Symbolic AIComputer Vision
 
Why Gradient Clipping accelerates training for neural networks
Why Gradient Clipping accelerates training for neural networks
OptimizationEfficient AI
 
SenSR: the first practical algorithm for individual fairness
SenSR: the first practical algorithm for individual fairness
AI FairnessRobustness
 
Sign-OPT: Defending the hard-label black-box cyber attack
Sign-OPT: Defending the hard-label black-box cyber attack
CybersecurityAdversarial Machine Learning
 
Bio-Inspired Hashing for Unsupervised Similarity Search
Bio-Inspired Hashing for Unsupervised Similarity Search
ICMLNeuroscience
 
Universal Domain Adaptation through Self Supervision
Universal Domain Adaptation through Self Supervision
Transfer LearningUnsupervised Learning
 
MCUNet: Tiny Deep Learning on IoT Devices
MCUNet: Tiny Deep Learning on IoT Devices
Deep LearningEfficient AI
 
Approximate Cross-Validation for Structured Models
Approximate Cross-Validation for Structured Models
Bayesian Modeling
 
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
Computer VisionMultimodal Learning
 
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
NeurIPS
 
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
NeurIPS
 
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
Efficient AI
 
Continuous Regularized Wasserstein Barycenters
Continuous Regularized Wasserstein Barycenters
Optimal Transport
 
Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning
Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning
Efficient AI
 
Auxiliary Task Reweighting for Minimum-data Learning
Auxiliary Task Reweighting for Minimum-data Learning
NeurIPS
 
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
NeurIPS
 
Simulating a Primate Visual Cortex at the Front of CNNs Improves Robustness to Adversarial Attacks and Image Corruptions
Simulating a Primate Visual Cortex at the Front of CNNs Improves Robustness to Adversarial Attacks and Image Corruptions
Neuroscience
 
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
Bayesian Modeling
 
Training Stronger Baselines for Learning to Optimize
Training Stronger Baselines for Learning to Optimize
Optimization
 
Applications of Common Entropy in Causal Inference
Applications of Common Entropy in Causal Inference
Causal Inference
 
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Causal Inference
 
Entropic Causal Inference: Identifiability and Finite Sample Results
Entropic Causal Inference: Identifiability and Finite Sample Results
Causal Inference
 
Higher-Order Certification For Randomized Smoothing
Higher-Order Certification For Randomized Smoothing
Optimization
 
Debiased Contrastive Learning
Debiased Contrastive Learning
NeurIPS
 
Learning Restricted Boltzmann Machines With Sparse Latent Variables
Learning Restricted Boltzmann Machines With Sparse Latent Variables
NeurIPS
 
Differentiable Augmentation for Data-Efficient GAN Training
Differentiable Augmentation for Data-Efficient GAN Training
Optimization
 
Robust Federated Learning: The Case of Affine Distribution Shifts
Robust Federated Learning: The Case of Affine Distribution Shifts
Federated Learning
 
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
NeurIPS
 
Online Bayesian Goal Inference for Boundedly-Rational Planning Agents
Online Bayesian Goal Inference for Boundedly-Rational Planning Agents
NeurIPS
 
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
NeurIPS
 
Active Structure Learning of Causal DAGs via Directed Clique Trees
Active Structure Learning of Causal DAGs via Directed Clique Trees
Causal Inference
 
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
NeurIPS
 
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
NeurIPS
 
Testing Determinantal Point Processes
Testing Determinantal Point Processes
NeurIPS
 
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
NeurIPS
 
Learning Physical Graph Representations from Visual Scenes
Learning Physical Graph Representations from Visual Scenes
NeurIPS
 
Black Loans Matter: Fighting Bias for AI Fairness in Lending
Black Loans Matter: Fighting Bias for AI Fairness in Lending
AI FairnessAI in Finance
 
The Computational Limits of Deep Learning
The Computational Limits of Deep Learning
Efficient AIDeep Learning
 
Do Neural Networks Really Need to Be So Big?
Do Neural Networks Really Need to Be So Big?
Efficient AIDeep Learning
 
Can a Fruit Fly Learn Word Embeddings?
Can a Fruit Fly Learn Word Embeddings?
ICLR
 
Large Associative Memory Problem in Neurobiology and Machine Learning
Large Associative Memory Problem in Neurobiology and Machine Learning
ICLR