yusuke1997/dblp-id-title huggingface dataset:
InfoGCL: Information-Aware Graph Contrastive Learning
You Are the Best Reviewer of Your Own Papers: An Owner-Assisted Scoring Mechanism
Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
Strategies for Teaching Layered Networks Classification Tasks
Masked Generative Adversarial Networks are Data-Efficient Generation Learners
Statistical and Topological Properties of Sliced Probability Divergences
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
Adaptive Depth Networks with Skippable Sub-Paths
HNPE: Leveraging Global Parameters for Neural Posterior Estimation
Dirichlet Graph Variational Autoencoder
Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
A shooting formulation of deep learning
The phase diagram of approximation rates for deep neural networks
Optimization for Approximate Submodularity
Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning
Generalized Boosting
Distributed Weight Consolidation: A Brain Segmentation Case Study
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition
Measuring Shared Information and Coordinated Activity in Neuronal Networks
Multi-Object 3D Grounding with Dynamic Modules and Language-Informed Spatial Attention
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks
Differentiable Ranking and Sorting using Optimal Transport
Kernelized Cumulants: Beyond Kernel Mean Embeddings
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning
Sobolev Independence Criterion
What Makes and Breaks Safety Fine-tuning? A Mechanistic Study
Learning to Modulate pre-trained Models in RL
GramGAN: Deep 3D Texture Synthesis From 2D Exemplars
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search
DISK: Learning local features with policy gradient
Scaling Laws for Hyperparameter Optimization
ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation
Bayesian Optimization with Exponential Convergence
Multilingual Pre-training with Universal Dependency Learning
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
Not so griddy: Internal representations of RNNs path integrating more than one agent
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
New Approaches Towards Robust, Adaptive Speech Recognition (invited paper)
History distribution matching method for predicting effectiveness of HIV combination therapies
Simple strategies for recovering inner products from coarsely quantized random projections
Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models
AUC Optimization vs. Error Rate Minimization
The CLEAR Benchmark: Continual LEArning on Real-World Imagery
Quaternion Knowledge Graph Embeddings
Shape and Illumination from Shading using the Generic Viewpoint Assumption
Robust Estimation of Neural Signals in Calcium Imaging
What if Neural Networks had SVDs?
When are ensembles really effective?
Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing
On Completeness-aware Concept-Based Explanations in Deep Neural Networks
Block Coordinate Regularization by Denoising
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Unsupervised Feature Selection for the $k$-means Clustering Problem
Pure Exploration in Kernel and Neural Bandits
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
Transductive Inference for Estimating Values of Functions
Energy-Efficient Scheduling with Predictions
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction
HyperLogic: Enhancing Diversity and Accuracy in Rule Learning with HyperNets
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration
Partially Encrypted Deep Learning using Functional Encryption
SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting
Stochastic Expectation Propagation
Tempo tracking and rhythm quantization by sequential Monte Carlo
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings
A general framework for investigating how far the decoding process in the brain can be simplified
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss
Covariance Selection in the Linear Mixed Effect Mode
Practical No-box Adversarial Attacks against DNNs
AUC Maximization under Positive Distribution Shift
History-Dependent Attractor Neural Networks
LSTM can Solve Hard Long Time Lag Problems
Relational recurrent neural networks
A Bayesian Framework for Cross-Situational Word-Learning
Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Pre-trained Large Language Models Use Fourier Features to Compute Addition
Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text
Equivariant Manifold Flows
Adaptive Design Optimization in Experiments with People
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs
Non-metric Similarity Graphs for Maximum Inner Product Search
Fast Transformation-Invariant Factor Analysis
Inner-Outer Aware Reconstruction Model for Monocular 3D Scene Reconstruction
Rule Induction through Integrated Symbolic and Subsymbolic Processing
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation
Exact expressions for double descent and implicit regularization via surrogate random design
Large Language Models are Zero-Shot Reasoners
A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets
Alleviating the Semantic Gap for Generalized fMRI-to-Image Reconstruction
From Mixtures of Mixtures to Adaptive Transform Coding
Learning Hard Optimization Problems: A Data Generation Perspective
Oriented Non-Radial Basis Functions for Image Coding and Analysis
Introspective Classification with Convolutional Nets
Bidirectional Recurrent Neural Networks as Generative Models
Divergences between Language Models and Human Brains
Reputation-based Worker Filtering in Crowdsourcing
Unsupervised Causal Generative Understanding of Images
Molecule Design by Latent Prompt Transformer
Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning
Graph-Based Visual Saliency
Real-Time Computer Vision and Robotics Using Analog VLSI Circuits
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning
Shallow Updates for Deep Reinforcement Learning
Distributed Inverse Constrained Reinforcement Learning for Multi-agent Systems
Nearly Optimal Bounds for Cyclic Forgetting
Deep Molecular Representation Learning via Fusing Physical and Chemical Information
Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization
MetaSDF: Meta-Learning Signed Distance Functions
GCN meets GPU: Decoupling "When to Sample" from "How to Sample"
First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data
Discovering conflicting groups in signed networks
A Reduction for Efficient LDA Topic Reconstruction
DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes
Improving Diffusion-Based Image Synthesis with Context Prediction
RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
Structured Learning of Gaussian Graphical Models
Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
Stagewise Processing in Error-correcting Codes and Image Restoration
Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning
An Iterative Self-Learning Framework for Medical Domain Generalization
Hierarchical clustering with dot products recovers hidden tree structure
ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making
Adaptive Sampling for Stochastic Risk-Averse Learning
Online Learning in Contextual Bandits using Gated Linear Networks
Adaptive Neural Networks Using MOS Charge Storage
Towards the Dynamics of a DNN Learning Symbolic Interactions
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$
SETLEXSEM CHALLENGE: Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language Models
WhodunitBench: Evaluating Large Multimodal Agents via Murder Mystery Games
Parallelizing Support Vector Machines on Distributed Computers
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
Semantic uncertainty intervals for disentangled latent spaces
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models
Polynomial Neural Fields for Subband Decomposition and Manipulation
Incremental Algorithms for Hierarchical Classification
GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling
Robust Logistic Regression and Classification
Rankmax: An Adaptive Projection Alternative to the Softmax Function
F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators
Direct Unlearning Optimization for Robust and Safe Text-to-Image Models
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction
Towards a Combinatorial Characterization of Bounded-Memory Learning
Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization
LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward
Random Permutation Online Isotonic Regression
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL
Differentiable Quality Diversity
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
Improved Transformer for High-Resolution GANs
Regret Minimization in Stackelberg Games with Side Information
Reinforcement Learning with Neural Radiance Fields
Connectionism for Music and Audition
Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition
Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization
Training without training data: Improving the generalizability of automated medical abbreviation disambiguation
Neural Trees for Learning on Graphs
Cholinergic Modulation May Enhance Cortical Associative Memory Function
Grow and Merge: A Unified Framework for Continuous Categories Discovery
SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training
Combating Representation Learning Disparity with Geometric Harmonization
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning
Cooperative Inverse Reinforcement Learning
Why Go Full? Elevating Federated Learning Through Partial Network Updates
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex
Sampling Networks and Aggregate Simulation for Online POMDP Planning
Constrained deep neural network architecture search for IoT devices accounting for hardware calibration
Data Distribution Valuation
Fast Training of Neural Lumigraph Representations using Meta Learning
Baxter Permutation Process
Black Box Probabilistic Numerics
FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space
Planar Hidden Markov Modeling: From Speech to Optical Character Recognition
Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
DISCOVER: Making Vision Networks Interpretable via Competition and Dissection
Learning Bayesian Belief Networks with Neural Network Estimators
Uncertainty Aware Semi-Supervised Learning on Graph Data
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset
A Dirty Model for Multi-task Learning
Semiparametric Principal Component Analysis
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
A Randomized Algorithm to Reduce the Support of Discrete Measures
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization
Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
Word2Fun: Modelling Words as Functions for Diachronic Word Representation
Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation
ElasticMVS: Learning elastic part representation for self-supervised multi-view stereopsis
Optimal Scalarizations for Sublinear Hypervolume Regret
Blockwise Parallel Decoding for Deep Autoregressive Models
Tighter Bounds for Structured Estimation
PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising
Adam with Bandit Sampling for Deep Learning
Invertible Convolutional Flow
Causal Imitation for Markov Decision Processes: a Partial Identification Approach
Implicit Regularization in Deep Matrix Factorization
Dynamic Cell Structures
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks
Learning De-Biased Representations for Remote-Sensing Imagery
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization
Brain Inspired Reinforcement Learning
Combining Generative and Discriminative Models for Hybrid Inference
Associative Memory via a Sparse Recovery Model
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training
Out-Of-Distribution Detection with Diversification (Provably)
An experimental comparison of recurrent neural networks
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Bayesian active learning with localized priors for fast receptive field characterization
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
A Little Is Enough: Circumventing Defenses For Distributed Learning
A Refined Margin Distribution Analysis for Forest Representation Learning
Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps
REDUCR: Robust Data Downsampling using Class Priority Reweighting
Learning Multiple Tasks with Multilinear Relationship Networks
Putting Gale & Shapley to Work: Guaranteeing Stability Through Learning
Squeezeformer: An Efficient Transformer for Automatic Speech Recognition
Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud
On Convergence of Nearest Neighbor Classifiers over Feature Transformations
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Mechanism design augmented with output advice
Self-Guiding Exploration for Combinatorial Problems
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction
Zero-Shot 3D Drug Design by Sketching and Generating
A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
Learning from Mixtures of Private and Public Populations
Koopman Kernel Regression
Focus On What Matters: Separated Models For Visual-Based RL Generalization
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Kernels for Multi--task Learning
Few-shot Image Generation via Adaptation-Aware Kernel Modulation
Distribution Matching for Transduction
Information Re-Organization Improves Reasoning in Large Language Models
Is Learning The n-th Thing Any Easier Than Learning The First?
Robust Data-Driven Dynamic Programming
A Non-Parametric Approach to Dynamic Programming
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
CEIL: Generalized Contextual Imitation Learning
Neural Variational Inference and Learning in Undirected Graphical Models
An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem
Improved Moves for Truncated Convex Models
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
CultureLLM: Incorporating Cultural Differences into Large Language Models
Shapley Residuals: Quantifying the limits of the Shapley value for explanations
GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI
Circuit Optimization Predicts Dynamic Network for Chemosensory Orientation in the Nematode C. elegans
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Post-training Iterative Hierarchical Data Augmentation for Deep Networks
Robust and Decomposable Average Precision for Image Retrieval
GenEval: An object-focused framework for evaluating text-to-image alignment
Modeling Human Exploration Through Resource-Rational Reinforcement Learning
The representer theorem for Hilbert spaces: a necessary and sufficient condition
Black-box coreset variational inference
NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild
Path following algorithms for 𝓁 2 -regularized M-estimation with approximation guarantee
Near-optimal Differentially Private Principal Components
Bayesian Optimization with Gradients
Sequential Hypothesis Testing under Stochastic Deadlines
GLBench: A Comprehensive Benchmark for Graph with Large Language Models
Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing
Detecting Overfitting via Adversarial Examples
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
DOMINO: Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning
Randomized tests for high-dimensional regression: A more efficient and powerful solution
Online Non-convex Learning in Dynamic Environments
Real-time Stereo-based 3D Object Detection for Streaming Perception
Gaussian Kernel Mixture Network for Single Image Defocus Deblurring
Systematic Generalization with Edge Transformers
Variational Gaussian processes for linear inverse problems
Paradoxes in Fair Machine Learning
DAC: The Double Actor-Critic Architecture for Learning Options
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs
Benchmarking Counterfactual Image Generation
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
Decomposing Parameter Estimation Problems
Dynamics of On-Line Gradient Descent Learning for Multilayer Neural Networks
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
Envelope-based Planning in Relational MDPs
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
Posterior and Computational Uncertainty in Gaussian Processes
Toward Understanding Generative Data Augmentation
Are Diffusion Models Vision-And-Language Reasoners?
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA
A Model of Auditory Streaming
Geometry-Aware Adaptation for Pretrained Models
OpenDataVal: a Unified Benchmark for Data Valuation
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
On Strategy Stitching in Large Extensive Form Multiplayer Games
Extending Multi-modal Contrastive Representations
Blind Motion Deblurring Using Image Statistics
Derivatives of Stochastic Gradient Descent in parametric optimization
Adversarial Blocking Bandits
Variance Reduction in Bipartite Experiments through Correlation Clustering
Group Meritocratic Fairness in Linear Contextual Bandits
Variational Inference for Continuous-Time Switching Dynamical Systems
Bayesian Backprop in Action: Pruning, Committees, Error Bars and an Application to Spectroscopy
On the Sample Complexity of Learning under Geometric Stability
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
Stochastic Bandits with Context Distributions
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
Worst-case Loss Bounds for Single Neurons
BRITS: Bidirectional Recurrent Imputation for Time Series
Large-Margin Convex Polytope Machine
Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity
LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
Convergent Representations of Computer Programs in Human and Artificial Neural Networks
A Sequence Kernel and its Application to Speaker Recognition
Ambient Diffusion: Learning Clean Distributions from Corrupted Data
Functional Gradient Flows for Constrained Sampling
Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon
Probabilistic Inference of Speech Signals from Phaseless Spectrograms
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties
How Deep is the Feature Analysis underlying Rapid Visual Categorization?
GAP Safe Screening Rules for Sparse-Group Lasso
Deep Generalized Method of Moments for Instrumental Variable Analysis
HelpSteer 2: Open-source dataset for training top-performing reward models