yusuke1997/dblp-id-title huggingface dataset:
Differentially Private Approximate Near Neighbor Counting in High Dimensions
Benign overfitting in leaky ReLU networks with moderate input dimension
Stochastic Relational Models for Discriminative Link Prediction
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics
Convex Optimization Procedure for Clustering: Theoretical Revisit
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints
A Unified Sequence Interface for Vision Tasks
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs
A Delay-Line Based Motion Detection Chip
Bicriteria Multidimensional Mechanism Design with Side Information
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection
Multiple Relational Embedding
Neurosymbolic Transformers for Multi-Agent Communication
Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections
Exponential Family Harmoniums with an Application to Information Retrieval
Novelty Search in Representational Space for Sample Efficient Exploration
Twin Auxilary Classifiers GAN
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge
Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain
CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos
One-Shot Unsupervised Cross Domain Translation
PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond
Sequential Algorithms for Testing Closeness of Distributions
Stein Variational Gradient Descent With Matrix-Valued Kernels
A Unified Fast Gradient Clipping Framework for DP-SGD
Kernel Machines and Boolean Functions
Neural characterization in partially observed populations of spiking neurons
Efficient Bayesian network structure learning via local Markov boundary search
Holographic Recurrent Networks
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions
Inferring neural population dynamics from multiple partial recordings of the same neural circuit
Reward Imputation with Sketching for Contextual Batched Bandits
Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds
Instance-Dependent Partial Label Learning
Learning Trajectory Preferences for Manipulators via Iterative Improvement
WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
Identifying Outlier Arms in Multi-Armed Bandit
Rethinking Value Function Learning for Generalization in Reinforcement Learning
Spatial and anatomical regularization of SVM for brain image analysis
Dynamic Grained Encoder for Vision Transformers
Mean Field Methods for Classification with Gaussian Processes
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration
EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought
CLIP-It! Language-Guided Video Summarization
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
A Robust Non-Clairvoyant Dynamic Mechanism for Contextual Auctions
The Nonnegative Boltzmann Machine
A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation
Fractionally Predictive Spiking Neurons
How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
Online Market Equilibrium with Application to Fair Division
CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts
On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation
FEAST at Play: Feature ExtrAction using Score function Tensors
NeuralFluid: Nueral Fluidic System Design and Control with Differentiable Simulation
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object Detection
Optimizing Relevance Maps of Vision Transformers Improves Robustness
HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction
Against Edges: Function Approximation with Multiple Support Maps
CELLE-2: Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transformer
Amortized Active Causal Induction with Deep Reinforcement Learning
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD
Constraint-based Causal Structure Learning with Consistent Separating Sets
FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation
Translated Learning: Transfer Learning across Different Feature Spaces
Variational Dropout and the Local Reparameterization Trick
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Distributed Non-Stochastic Experts
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
Deep Hyperalignment
Training Deep Neural Networks with 8-bit Floating Point Numbers
Minimizers of the Empirical Risk and Risk Monotonicity
Non-deep Networks
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach
Reinforcement Learning for Trading
Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs
Learning symmetries via weight-sharing with doubly stochastic tensors
Flexible mapping of abstract domains by grid cells via self-supervised extraction and projection of generalized velocity signals
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
Revisiting Active Sets for Gaussian Process Decoders
Spikernels: Embedding Spiking Neurons in Inner-Product Spaces
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
Foraging in an Uncertain Environment Using Predictive Hebbian Learning
Matrix Compression via Randomized Low Rank and Low Precision Factorization
Stochastic Dynamics of Three-State Neural Networks
Handling Long-tailed Feature Distribution in AdderNets
Towards understanding retrosynthesis by energy-based models
Fully Distributed, Flexible Compositional Visual Representations via Soft Tensor Products
The Human Kernel
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Robustness Guarantees for Adversarially Trained Neural Networks
On Regularizing Rademacher Observation Losses
Cascade of phase transitions in the training of energy-based models
New Subsampling Algorithms for Fast Least Squares Regression
Performance of Kullback-Leibler Based Expert Opinion Pooling for Unlikely Events
Learning sparse codes from compressed representations with biologically plausible local wiring constraints
Numerical Composition of Differential Privacy
Synthetic Experience Replay
VLSI Implementation of a High-Capacity Neural Network Associative Memory
AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions
Graph Neural Networks with Adaptive Readouts
Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning
Adaptive Classification for Prediction Under a Budget
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Accelerating Non-Maximum Suppression: A Graph Theory Perspective
The Art of Saying No: Contextual Noncompliance in Language Models
Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems
LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Generating more realistic images using gated MRF's
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Fair Adaptive Experiments
Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds
What is a Good Metric to Study Generalization of Minimax Learners?
Computing Robust Counter-Strategies
SE(3) Equivariant Augmented Coupling Flows
Variational EM Algorithms for Non-Gaussian Latent Variable Models
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity
Entropic Neural Optimal Transport via Diffusion Processes
Structure of universal formulas
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning
Tensor Program Optimization with Probabilistic Programs
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
Sketch-Based Linear Value Function Approximation
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
On the Generative Utility of Cyclic Conditionals
Grid Saliency for Context Explanations of Semantic Segmentation
Active Learning with Statistical Models
Tractable Learning for Complex Probability Queries
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium
Learning Affordance Landscapes for Interaction Exploration in 3D Environments
Multi-Task Learning for Stock Selection
Incorporating Invariances in Non-Linear Support Vector Machines
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration
Reinforcement Learning with Hierarchies of Machines
HuRef: HUman-REadable Fingerprint for Large Language Models
Self-Supervised Visual Representation Learning with Semantic Grouping
Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents
Adaptive Experimentation When You Can't Experiment
Minimum Entropy Coupling with Bottleneck
MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity Parsing
Learning Human-like Representations to Enable Learning Human Values
Models Wanted: Must Fit Dimensions of Sleep and Dreaming
A sharp NMF result with applications in network modeling
Bayesian Network Score Approximation using a Metagraph Kernel
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval
Higher-Order Causal Message Passing for Experimentation with Complex Interference
SHAP-IQ: Unified Approximation of any-order Shapley Interactions
Neural Proximal Gradient Descent for Compressive Imaging
Can Simple Cells Learn Curves? A Hebbian Model in a Structured Environment
Analog VLSI Processor Implementing the Continuous Wavelet Transform
DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery
Asymptotic Universality for Learning Curves of Support Vector Machines
Fair regression with Wasserstein barycenters
Analytical Results for the Error in Filtering of Gaussian Processes
A Theoretical View on Sparsely Activated Networks
Constants of motion network
Multi-mapping Image-to-Image Translation via Learning Disentanglement
Tractable Regularization of Probabilistic Circuits
Learning Neural Acoustic Fields
Improved Graph Laplacian via Geometric Self-Consistency
Detrended Partial Cross Correlation for Brain Connectivity Analysis
Simplified and Generalized Masked Diffusion for Discrete Data
Higher-Order Certification For Randomized Smoothing
Learning Mixtures of Submodular Functions for Image Collection Summarization
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation
Lossy Image Compression with Conditional Diffusion Models
Phase Transitions in Neural Networks
Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding
Learning Mixed Multinomial Logit Model from Ordinal Data
Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks
Explaining Deep Learning Models - A Bayesian Non-parametric Approach
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
Kernel Identification Through Transformers
Transferable Adversarial Attacks on SAM and Its Downstream Models
Bayesian Modeling of Human Concept Learning
Uncertainty-based Continual Learning with Adaptive Regularization
Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
Model-Based Reinforcement Learning via Imagination with Derived Memory
Hamiltonian Variational Auto-Encoder
On Infinite Separations Between Simple and Optimal Mechanisms
Boosting Text-to-Video Generative Model with MLLMs Feedback
Counterfactual Memorization in Neural Language Models
Factoring nonnegative matrices with linear programs
Overlapping Spaces for Compact Graph Representations
Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images
CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions
See More for Scene: Pairwise Consistency Learning for Scene Classification
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning
RSN: Randomized Subspace Newton
Synthesizing Tasks for Block-based Programming
Semantic Diffusion Network for Semantic Segmentation
DiTFastAttn: Attention Compression for Diffusion Transformer Models
MambaTree: Tree Topology is All You Need in State Space Model
EMR-Merging: Tuning-Free High-Performance Model Merging
Advances in Neural Information Processing Systems 1, [NIPS Conference, Denver, Colorado, USA, 1988]
Synchronization and Grammatical Inference in an Oscillating Elman Net
NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos
Diffusion-based Curriculum Reinforcement Learning
Randomized Truthful Auctions with Learning Agents
Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa
Multiple-Play Bandits in the Position-Based Model
Hierarchically Gated Recurrent Neural Network for Sequence Modeling
Describing Visual Scenes using Transformed Dirichlet Processes
Parametric Task Learning
Visual Fourier Prompt Tuning
Supervised Multimodal Bitransformers for Classifying Images and Text
Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling
The Limits of Optimal Pricing in the Dark
Subset Selection by Pareto Optimization
Play to Grade: Testing Coding Games as Classifying Markov Decision Process
Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation
Dense Associative Memory for Pattern Recognition
Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features
Zero-Shot Reinforcement Learning from Low Quality Data
Stochastic Neurodynamics
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models
An Unbiased Risk Estimator for Learning with Augmented Classes
SpiderBoost and Momentum: Faster Variance Reduction Algorithms
Anytime Model Selection in Linear Bandits
A StrongREJECT for Empty Jailbreaks
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model
The Sparse Manifold Transform
More data speeds up training time in learning halfspaces over sparse vectors
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations
Approximate Cross-Validation with Low-Rank Data in High Dimensions
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions
NovelD: A Simple yet Effective Exploration Criterion
Two-Dimensional Object Localization by Coarse-to-Fine Correlation Matching
Lifted Relational Neural Networks
PTQD: Accurate Post-Training Quantization for Diffusion Models
Safe Exploration for Interactive Machine Learning
Computational Separations between Sampling and Optimization
Train-Attention: Meta-Learning Where to Focus in Continual Knowledge Learning
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
Discriminative State Space Models
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model
Multi-agent Dynamic Algorithm Configuration
Relative stability toward diffeomorphisms indicates performance in deep nets
PyGlove: Symbolic Programming for Automated Machine Learning
Natural Value Approximators: Learning when to Trust Past Estimates
Efficient Rematerialization for Deep Networks
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
One-Step Effective Diffusion Network for Real-World Image Super-Resolution
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy
An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
TFG: Unified Training-Free Guidance for Diffusion Models
Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere
On the Saturation Effects of Spectral Algorithms in Large Dimensions
Video Timeline Modeling For News Story Understanding
Robust Regression Revisited: Acceleration and Improved Estimation Rates
Private Estimation with Public Data
Lesan - Machine Translation for Low Resource Languages
Online Classification for Complex Problems Using Simultaneous Projections
Using Local Models to Control Movement
Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks
Combinatorial Inference against Label Noise
Formalizing the Generalization-Forgetting Trade-off in Continual Learning
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection
VisCo Grids: Surface Reconstruction with Viscosity and Coarea Grids
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms
Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly
Multi-Stage Influence Function
The Power of Resets in Online Reinforcement Learning
Towards closing the gap between the theory and practice of SVRG
From Trainable Negative Depth to Edge Heterophily in Graphs
FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Biomedical Visual Instruction Tuning with Clinician Preference Alignment
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
Operator Splitting Value Iteration
Learning Exponential Families from Truncated Samples
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
Robustness in Markov Decision Problems with Uncertain Transition Matrices
Identification of Gaussian Process State Space Models
Unsupervised learning of an efficient short-term memory network
Nearly Optimal Approximation of Matrix Functions by the Lanczos Method
Deductive Verification of Chain-of-Thought Reasoning
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization
Convex Tensor Decomposition via Structured Schatten Norm Regularization
Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
Understanding the Under-Coverage Bias in Uncertainty Estimation
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition
Efficient Unsupervised Learning for Localization and Detection in Object Categories
Outlier-Robust Gromov-Wasserstein for Graph Data
A Self Validation Network for Object-Level Human Attention Estimation
Goal-Based Imitation as Probabilistic Inference over Graphical Models
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
RényiCL: Contrastive Representation Learning with Skew Rényi Divergence
Class-agnostic Reconstruction of Dynamic Objects from Videos
Learning Latent Seasonal-Trend Representations for Time Series Forecasting
Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes
Dynamic Regret of Convex and Smooth Functions
Bandits with Preference Feedback: A Stackelberg Game Perspective
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching
Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras
Estimating Koopman operators with sketching to provably learn large scale dynamical systems
Policy Improvement via Imitation of Multiple Oracles
Neural optimal feedback control with local learning rules
Disentangled behavioural representations
Systematic Visual Reasoning through Object-Centric Relational Abstraction
F1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning
Formulating Robustness Against Unforeseen Attacks
A Comprehensive Benchmark for Neural Human Radiance Fields
A Novel Approach to Prediction of the 3-Dimensional Structures
Human memory search as a random walk in a semantic network
Information is Power: Intrinsic Control via Information Capture
Dynamic Sparsity Is Channel-Level Sparsity Learner
LucidAction: A Hierarchical and Multi-model Dataset for Comprehensive Action Quality Assessment
Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient
The Power of Comparisons for Actively Learning Linear Classifiers
Optimal cross-learning for contextual bandits with unknown context distributions
Optimal Neural Spike Classification
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Neural Topological Ordering for Computation Graphs
Geometry Based Data Generation
Minimax Estimation of Neural Net Distance
Trade-off Between Efficiency and Consistency for Removal-based Explanations
Multitask Learning without Label Correspondences
Uncertainty Quantification for Inferring Hawkes Networks
ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections
Image Parsing with Stochastic Scene Grammar
Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy
Learning to Segment Object Candidates
Online Forecasting of Total-Variation-bounded Sequences
Grounding inductive biases in natural images: invariance stems from variations in data
Conic Scan-and-Cover algorithms for nonparametric topic modeling
TAP-Vid: A Benchmark for Tracking Any Point in a Video
Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers
Approximate Inference and Protein-Folding
FLEX: Unifying Evaluation for Few-Shot NLP
Analysis of SVM with Indefinite Kernels
Boundary Matters: A Bi-Level Active Finetuning Method
A Machine Learning Approach to Conjoint Analysis