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Bio-Inspired Hashing for Unsupervised Similarity Search
Bio-Inspired Hashing for Unsupervised Similarity Search
 
SenSR: the first practical algorithm for individual fairness
SenSR: the first practical algorithm for individual fairness
 
Why Gradient Clipping accelerates training for neural networks
Why Gradient Clipping accelerates training for neural networks
 
CLEVRER: The first video dataset for neuro-symbolic reasoning
CLEVRER: The first video dataset for neuro-symbolic reasoning
 
Fast and efficient black-box testing for AI cybersecurity
Fast and efficient black-box testing for AI cybersecurity
 
Layer-wise federated learning with FedMA
Layer-wise federated learning with FedMA
 
Learning Rate Rewinding for elegant neural network pruning
Learning Rate Rewinding for elegant neural network pruning
 
Implementation Matters in Deep RL: A Case Study on PPO and TRPO
Implementation Matters in Deep RL: A Case Study on PPO and TRPO
 
Once for All: Train One Network and Specialize it for Efficient Deployment
Once for All: Train One Network and Specialize it for Efficient Deployment
 
Deep Audio Priors Emerge From Harmonic Convolutional Networks
Deep Audio Priors Emerge From Harmonic Convolutional Networks
 
A Closer Look at Deep Policy Gradients
A Closer Look at Deep Policy Gradients
 
Deep Symbolic Superoptimization Without Human Knowledge
Deep Symbolic Superoptimization Without Human Knowledge
 
Reshaping Diverse Planning
Reshaping Diverse Planning
 
Adversarial Robustness vs Model Compression, or Both?
Adversarial Robustness vs Model Compression, or Both?
 
Point-Voxel CNN for Efficient 3D Deep Learning
Point-Voxel CNN for Efficient 3D Deep Learning
 
CASTER: An AI framework for preventing adverse reactions to medication
CASTER: An AI framework for preventing adverse reactions to medication
 
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
 
Reasoning about Human-Object Interactions through Dual Attention Networks
Reasoning about Human-Object Interactions through Dual Attention Networks
 
LaSO: Label-Set Operations networks for multi-label few-shot learning
LaSO: Label-Set Operations networks for multi-label few-shot learning
 
SpotTune: Transfer Learning through Adaptive Fine-tuning
SpotTune: Transfer Learning through Adaptive Fine-tuning
 
RepMet: Representative-based metric learning for classification and one-shot object detection
RepMet: Representative-based metric learning for classification and one-shot object detection
 
ObjectNet: A bias-controlled dataset object recognition
ObjectNet: A bias-controlled dataset object recognition
 
Moments in Time Dataset: one million videos for event understanding
Moments in Time Dataset: one million videos for event understanding
 
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
 
Self-supervised Moving Vehicle Tracking with Stereo Sound
Self-supervised Moving Vehicle Tracking with Stereo Sound
 
The sound of motions
The sound of motions
 
TSM: Temporal Shift Module for Efficient Video Understanding
TSM: Temporal Shift Module for Efficient Video Understanding
 
Graph Convolutional Networks for Temporal Action Localization
Graph Convolutional Networks for Temporal Action Localization
 
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
 
Online AI planning with graph neural networks and adaptive scheduling
Online AI planning with graph neural networks and adaptive scheduling
 
Reading between the lines with graph deep learning for NLP
Reading between the lines with graph deep learning for NLP
 
A unifying framework for expectation-aware AI planning
A unifying framework for expectation-aware AI planning
 
Automating machine learning with a joint selection framework
Automating machine learning with a joint selection framework
 
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
 
Embedding Compression with Isotropic Iterative Quantization
Embedding Compression with Isotropic Iterative Quantization
 
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
 
ZO-AdaMM: Derivative-free optimization for black-box problems
ZO-AdaMM: Derivative-free optimization for black-box problems
 
Big-Little-Video-Net: Work smarter, not harder, for video understanding
Big-Little-Video-Net: Work smarter, not harder, for video understanding
 
Topics are more meaningful than words. AI for comparative literature.
Topics are more meaningful than words. AI for comparative literature.
 
Imitation learning from observations
Imitation learning from observations
 
Using geometry to understand documents
Using geometry to understand documents
 
SPAHM: Parameter matching for model fusion
SPAHM: Parameter matching for model fusion
 
Alleviating label switching with optimal transport
Alleviating label switching with optimal transport
 
Visual Concept-Metaconcept Learning
Visual Concept-Metaconcept Learning
 
Causal inference is expensive. Here’s an algorithm for fixing that.
Causal inference is expensive. Here’s an algorithm for fixing that.
 
New tricks from old dogs: multi-source transfer learning
New tricks from old dogs: multi-source transfer learning
 
Reverse-engineering causal graphs with soft interventions
Reverse-engineering causal graphs with soft interventions
 
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
SimVAE: Simulator-Assisted Training for Interpretable Generative Models
 
Cross-channel Communication Networks
Cross-channel Communication Networks
 
The Future of Work: How New Technologies Are Transforming Tasks
The Future of Work: How New Technologies Are Transforming Tasks
 
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
 
Seeing What a GAN Cannot Generate
Seeing What a GAN Cannot Generate
 
Watch, Reason and Code: Learning to Represent Videos Using Program
Watch, Reason and Code: Learning to Represent Videos Using Program
 
Defensive Quantization: When Efficiency Meets Robustness
Defensive Quantization: When Efficiency Meets Robustness
 
Neural language models as psycholinguistic subjects: Representations of syntactic state
Neural language models as psycholinguistic subjects: Representations of syntactic state
 
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
 
Deep Leakage from Gradients
Deep Leakage from Gradients
 
Write, Execute, Assess: Program Synthesis with a REPL
Write, Execute, Assess: Program Synthesis with a REPL
 
Variational Russian Roulette for Deep Bayesian Nonparametrics
Variational Russian Roulette for Deep Bayesian Nonparametrics
 
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
 
Bayesian Nonparametric Federated Learning of Neural Networks
Bayesian Nonparametric Federated Learning of Neural Networks
 
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
 
Unsupervised learning by competing hidden units
Unsupervised learning by competing hidden units
 
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
 
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies
 
Tight Certificates of Adversarial Robustness
Tight Certificates of Adversarial Robustness
 
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
 
Weakly Supervised Dense Event Captioning in Videos
Weakly Supervised Dense Event Captioning in Videos
 
Neural Network Robustness Certification with General Activation Functions
Neural Network Robustness Certification with General Activation Functions
 
Scalable Graph Learning for Anti-Money Laundering: A First Look
Scalable Graph Learning for Anti-Money Laundering: A First Look
 
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
 
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
 
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems
 
Unsupervised learning with contrastive latent variable models
Unsupervised learning with contrastive latent variable models
 
Co-regularized Alignment for Unsupervised Domain Adaptation
Co-regularized Alignment for Unsupervised Domain Adaptation
 
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
 
Experimental Design for Cost-Aware Learning of Causal Graphs
Experimental Design for Cost-Aware Learning of Causal Graphs
 
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
 
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
 
signSGD via Zeroth-Order Oracle
signSGD via Zeroth-Order Oracle
 
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
 
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
 
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
 
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
 
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Delta-encoder: an effective sample synthesis method for few-shot object recognition
 
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
 
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
 
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
 
Dialog-based Interactive Image Retrieval
Dialog-based Interactive Image Retrieval
 
Learning to Teach in Cooperative Multiagent Reinforcement Learning
Learning to Teach in Cooperative Multiagent Reinforcement Learning
 
Learning to Separate Object Sounds by Watching Unlabeled Video
Learning to Separate Object Sounds by Watching Unlabeled Video
 
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
 
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
 
BlockDrop: Dynamic Inference Paths in Residual Networks
BlockDrop: Dynamic Inference Paths in Residual Networks
 
Action Centered Contextual Bandits
Action Centered Contextual Bandits
 
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
 
Gradient Descent for Spiking Neural Networks
Gradient Descent for Spiking Neural Networks
 
Ensemble Estimation of Information Divergence
Ensemble Estimation of Information Divergence