Kumar Avinava Dubey
22 papers · 2014–2025 · 6 conferences · across top CS/AI conferences
Achievements
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(5)
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(55)
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(6)
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Keyword Collector
(87)
Conferences
NIPS (9)
AISTATS (5)
ICLR (4)
ICML (2)
CORL (1)
EMNLP (1)
Top co-authors
Keywords
kernel approximation
(2)
hierarchical clustering
(2)
softmax kernel
(2)
fourier transform
(2)
transformer architecture
(2)
gaussian kernel
(2)
variance reduction
(2)
random feature
(2)
bayesian nonparametrics
(1)
graph theory
(1)
metric learning
(1)
relation extraction
(1)
question answering
(1)
language modeling
(1)
parameter estimation
(1)
bayesian inference
(1)
learning theory
(1)
point cloud
(1)
neural network optimization
(1)
approximate inference
(1)
Papers
Linear Transformer Topological Masking with Graph Random Features
ICLR 2025
Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
ICML 2025
Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs
AISTATS 2025
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
ICLR 2025
Fundamental Limits of Perfect Concept Erasure
AISTATS 2025
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
ICLR 2024
Scalable Neural Network Kernels
ICLR 2024
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
AISTATS 2024
Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning
EMNLP 2024
Efficient Graph Field Integrators Meet Point Clouds
ICML 2023
Robust Concept Erasure via Kernelized Rate-Distortion Maximization
NIPS 2023
Mnemosyne: Learning to Train Transformers with Transformers
NIPS 2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
CORL 2023
Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel
NIPS 2023
Chefs' Random Tables: Non-Trigonometric Random Features
NIPS 2022
A Fourier Approach to Mixture Learning
NIPS 2022
DAG-Structured Clustering by Nearest Neighbors
AISTATS 2021
Distributed, partially collapsed MCMC for Bayesian Nonparametrics
AISTATS 2020
Big Bird: Transformers for Longer Sequences
NIPS 2020
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
NIPS 2018
Variance Reduction in Stochastic Gradient Langevin Dynamics
NIPS 2016
Dependent nonparametric trees for dynamic hierarchical clustering
NIPS 2014