:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Mishra, Cyan Subhra, Chaudhary, Deeksha, Sampson, Jack, Knademir, Mahmut Taylan, Das, Chita
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2408.13696
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Salient Store: Enabling Smart Storage for Continuous Learning Edge Servers
by: Mishra, Cyan Subhra, et al.
Published: (2024)

Synergistic and Efficient Edge-Host Communication for Energy Harvesting Wireless Sensor Networks
by: Mishra, Cyan Subhra, et al.
Published: (2024)

Pushing the Performance Envelope of DNN-based Recommendation Systems Inference on GPUs
by: Jain, Rishabh, et al.
Published: (2024)

Parallel Context Compaction for Long-Horizon LLM Agent Serving
by: Cim, Musa, et al.
Published: (2026)

Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs
by: Lin, Jun-Liang, et al.
Published: (2026)

GPU Cluster Scheduling for Network-Sensitive Deep Learning
by: Sharma, Aakash, et al.
Published: (2024)

AsymVLM: Asymmetric Token Pruning for Efficient Vision-Language Model Inference
by: Feng, Yilin, et al.
Published: (2026)

Revisiting Generalization Power of a DNN in Terms of Symbolic Interactions
by: Cheng, Lei, et al.
Published: (2025)

Energy-Aware Decentralized Learning with Intermittent Model Training
by: Dhasade, Akash, et al.
Published: (2024)

Pretraining large language models with MXFP4 on Native FP4 Hardware
by: Cim, Musa, et al.
Published: (2026)

Energy-Aware DNN Graph Optimization
by: Wang, Yu, et al.
Published: (2020)

DNN Modularization via Activation-Driven Training
by: Ngo, Tuan, et al.
Published: (2024)

Diversifying Support Vector Machines for Boosting using Kernel Perturbation: Applications to Class Imbalance and Small Disjuncts
by: Datta, Shounak, et al.
Published: (2017)

MAx-DNN: Multi-Level Arithmetic Approximation for Energy-Efficient DNN Hardware Accelerators
by: Leon, Vasileios, et al.
Published: (2025)

Improving Conditional VAE with Non-Volume Preserving transformations
by: De, Tuhin Subhra
Published: (2025)

Rethinking the Potential of Layer Freezing for Efficient DNN Training
by: Yang, Chence, et al.
Published: (2025)

NeFT: Negative Feedback Training to Improve Robustness of Compute-In-Memory DNN Accelerators
by: Qin, Yifan, et al.
Published: (2023)

Exploring Variance Reduction in Importance Sampling for Efficient DNN Training
by: Kutsuna, Takuro
Published: (2025)

DecTrain: Deciding When to Train a Monocular Depth DNN Online
by: Fu, Zih-Sing, et al.
Published: (2024)

Joint Memory Frequency and Computing Frequency Scaling for Energy-efficient DNN Inference
by: Han, Yunchu, et al.
Published: (2025)

Optimizing DNN Inference on Multi-Accelerator SoCs at Training-time
by: Risso, Matteo, et al.
Published: (2024)

S7: Selective and Simplified State Space Layers for Sequence Modeling
by: Soydan, Taylan, et al.
Published: (2024)

Efficient and Provable Algorithms for Covariate Shift
by: Adil, Deeksha, et al.
Published: (2025)

MLTCP: Congestion Control for DNN Training
by: Rajasekaran, Sudarsanan, et al.
Published: (2024)

Accuracy Booster: Enabling 4-bit Fixed-point Arithmetic for DNN Training
by: Harma, Simla Burcu, et al.
Published: (2022)

NMS: Efficient Edge DNN Training via Near-Memory Sampling on Manifolds
by: Zhao, Boran, et al.
Published: (2025)

PaSE: Parallelization Strategies for Efficient DNN Training
by: Elango, Venmugil
Published: (2024)

Mirage: An RNS-Based Photonic Accelerator for DNN Training
by: Demirkiran, Cansu, et al.
Published: (2023)

Bayesian uncertainty-aware deep learning with noisy labels: Tackling annotation ambiguity in EEG seizure detection
by: Shama, Deeksha M., et al.
Published: (2024)

Parallelization Strategies for Dense LLM Deployment: Navigating Through Application-Specific Tradeoffs and Bottlenecks
by: Topcu, Burak, et al.
Published: (2026)

Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations
by: Esmaeilzadeh, Hadi, et al.
Published: (2023)

Distributionally Robust K-Means Clustering
by: Malik, Vikrant, et al.
Published: (2026)

Attractor-merging Crises and Intermittency in Reservoir Computing
by: Kabayama, Tempei, et al.
Published: (2025)

ProdRev: A DNN framework for empowering customers using generative pre-trained transformers
by: Gupta, Aakash, et al.
Published: (2025)

Dynamics of Learning: Generative Schedules from Latent ODEs
by: Sampson, Matt L., et al.
Published: (2025)

DAISM: Digital Approximate In-SRAM Multiplier-based Accelerator for DNN Training and Inference
by: Sonnino, Lorenzo, et al.
Published: (2023)

AdapSNE: Adaptive Fireworks-Optimized and Entropy-Guided Dataset Sampling for Edge DNN Training
by: Zhao, Boran, et al.
Published: (2025)

Revisiting Training Scale: An Empirical Study of Token Count, Power Consumption, and Parameter Efficiency
by: Dwyer, Joe
Published: (2026)

Explaining Generalization Power of a DNN Using Interactive Concepts
by: Zhou, Huilin, et al.
Published: (2023)

Towards Hardware Supported Domain Generalization in DNN-Based Edge Computing Devices for Health Monitoring
by: Loh, Johnson, et al.
Published: (2025)